Data/AI

Data/AI


Below are the associated Work Roles. Click the arrow to expand/collapse the Work Role information and view the associated Core and Additional KSATs (Knowledge, Skills, Abilties, and Tasks). Items denoted by a * are CORE KSATs for every Work Role, while other CORE KSATs vary by Work Role. Click on the other blue links to further explore the information.
AI Adoption Specialist Work Role ID: 753 (NIST: N/A) Workforce Element: Data/AI

Facilitates AI adoption by supporting the users of AI-enabled solutions.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
466A

Consult with customers and key stakeholders to evaluate functional requirements for AI and data applications.

Task
479A

Correlates training and learning to business or mission requirements.

Task
538

Develop new or identify existing awareness and training materials that are appropriate for intended audiences.

Task
918

Ability to prepare and deliver education and awareness briefings to ensure that systems, network, and data users are aware of and adhere to systems security policies and procedures.

Ability
1000B

Ensure that AI design and development activities are properly documented and updated.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
3022

Ability to communicate complex information, concepts, or ideas in a confident and well-organized manner through verbal, written, and/or visual means.

Ability
5380

Gather feedback on customer satisfaction and internal service performance to foster continual improvement.

Task
5430

Present technical information to technical and non-technical audiences.

Task
5843

Analyze national security/DoD mission priorities and gaps suitable for the application of AI solutions.

Task
5861

Coordinate with change management employees to plan, foster, and track change.

Task
5891

Identify viable AI projects based on organizational needs.

Task
5892

Identify ways to lead and motivate people to adopt AI solutions through cultural, organizational, or other types of change.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5909

Promote awareness of AI limitations and benefits.

Task
5918

Support an AI adoption strategy that aligns with the organization’s vision, mission, and goals.

Task
5921

Test how users interact with AI solutions.

Task
6311

Knowledge of machine learning theory and principles.

Knowledge
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6915A

Skill in communicating with all levels of the organization, including senior/mid-level executives, and operational-level personnel (e.g., interpersonal skills, approachability, effective listening skills, appropriate use of style and language for the audience).

Skill
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7001

Ability to inspire and lead a culture of innovation.

Ability
7003

Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.

Knowledge
7008

Knowledge of change models and frameworks.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7021

Knowledge of emerging trends and future use cases of AI.

Knowledge
7024

Knowledge of how AI is developed and operated.

Knowledge
7027

Knowledge of how humans interact with and/or are impacted by AI solutions within the DoD context.

Knowledge
7031

Knowledge of how to structure and display data.

Knowledge
7032

Knowledge of how to use data to tell a story.

Knowledge
7033

Knowledge of human factor engineering.

Knowledge
7037

Knowledge of machine learning operations (MLOps) processes and best practices.

Knowledge
7045

Knowledge of the AI lifecycle.

Knowledge
7046

Knowledge of the basic requirements for the successful delivery of AI solutions.

Knowledge
7047

Knowledge of the basics of customer experience, customer design, psychology of customer decision-making, and human-computer interaction.

Knowledge
7048

Knowledge of the benefits and limitations of AI capabilities.

Knowledge
7051

Knowledge of the possible impacts of machine learning blind spots and edge cases.

Knowledge
7053

Knowledge of the user experience (e.g., decision making, user design, and human-computer interaction) as it relates to AI systems.

Knowledge
7058

Skill in communicating AI and/or machine learning solutions to a wide range of audiences.

Skill
7065

Skill in explaining AI concepts and terminology.

Skill
7072

Skill in leading AI adoption efforts.

Skill

Additional KSATs

KSAT ID Description KSAT
942

Knowledge of the organization’s core business/mission processes.

Knowledge
5925

Use knowledge of business processes to create or recommend AI solutions.

Task
5861

Coordinate with change management employees to plan, foster, and track change.

Task
5880

Engage and collaborate with allies and partners to advance shared strategic AI objectives.

Task
6380

Knowledge of principles and processes for conducting training and education needs assessment.

Knowledge
7013

Knowledge of customer mission priorities and capabilities, as related to the integration and adoption of AI solutions.

Knowledge
7033

Knowledge of human factor engineering.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7041

Knowledge of remedies against unintended bias in AI solutions.

Knowledge
AI Innovation Leader Work Role ID: 902 (NIST: N/A) Workforce Element: Data/AI

Builds the organization’s AI vision and plan and leads policy and doctrine formation including how AI solutions can or will be used.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
391A

Acquire and manage the necessary resources, including leadership support, financial resources, infrastructure, and key personnel, to support AI innovation adoption goals and objectives.

Task
395A

Advise senior management on risk levels, security posture, and necessary changes to existing AI policies.​

Task
492B

Design and integrate an AI adoption strategy that supports the organization’s vision, mission, and goals.

Task
524

Develop and maintain strategic plans.

Task
629B

Identify and address AI workforce planning and management issues (e.g., recruitment, retention, and training).

Task
680B

Oversee AI budget, staffing, and contracting decisions.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
2416

Facilitate interactions between internal and external partner decision makers to synchronize and integrate courses of action in support of objectives.

Task
2558

Maintain relationships with internal and external partners involved in cyber planning or related areas.

Task
2624A

Conduct long-range, strategic planning efforts with internal and external partners to support AI capability development and use.

Task
3591

Knowledge of organization objectives, leadership priorities, and decision-making risks.

Knowledge
5843

Analyze national security/DoD mission priorities and gaps suitable for the application of AI solutions.

Task
5845

Appoint and guide a multidisciplinary team of AI experts to identify and assess risk throughout the AI development lifecycle.

Task
5849

Assess value of implemented AI projects based on organizational metrics.

Task
5862

Create and/or maintain governance structure for oversight and accountability of AI solutions.

Task
5879

Direct and/or support organizational and project-level AI risk management activities.

Task
5880

Engage and collaborate with allies and partners to advance shared strategic AI objectives.

Task
5882

Establish and/or maintain processes to ensure Responsible AI practices are reflected in an organization’s approach to AI acquisition, development, and deployment.

Task
5883

Evaluate and develop AI workforce structure resources and requirements.

Task
5887

Identify and address key roadblocks to AI implementation.

Task
5891

Identify viable AI projects based on organizational needs.

Task
5892

Identify ways to lead and motivate people to adopt AI solutions through cultural, organizational, or other types of change.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5909

Promote awareness of AI limitations and benefits.

Task
5913

Remove barriers to data acquisition, collection, and curation efforts required for AI solutions.

Task
6040

Ability to assess and forecast manpower requirements to meet organizational objectives.

Ability
6250

Knowledge of Workforce Framework, work roles, and associated tasks, knowledge, skills, and abilities.

Knowledge
6311

Knowledge of machine learning theory and principles.

Knowledge
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6915A

Skill in communicating with all levels of the organization, including senior/mid-level executives, and operational-level personnel (e.g., interpersonal skills, approachability, effective listening skills, appropriate use of style and language for the audience).

Skill
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7000

Ability to identify, connect, and influence key stakeholders to speed AI adoption.

Ability
7001

Ability to inspire and lead a culture of innovation.

Ability
7003

Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.

Knowledge
7007

Knowledge of best practices in organizational conflict management.

Knowledge
7014

Knowledge of data acquisition, collection, and curation best practices required for AI solutions.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7021

Knowledge of emerging trends and future use cases of AI.

Knowledge
7024

Knowledge of how AI is developed and operated.

Knowledge
7034

Knowledge of interactions and integration of DataOps, MLOps, and DevSecOps in AI.

Knowledge
7042

Knowledge of resources and capabilities required to complete AI projects.

Knowledge
7043

Knowledge of staffing, contracting, and budgetary requirements to run an AI-enabled organization.

Knowledge
7045

Knowledge of the AI lifecycle.

Knowledge
7046

Knowledge of the basic requirements for the successful delivery of AI solutions.

Knowledge
7048

Knowledge of the benefits and limitations of AI capabilities.

Knowledge
7050

Knowledge of the nature and function of technology platforms and tools used to create and employ AI.

Knowledge
7058

Skill in communicating AI and/or machine learning solutions to a wide range of audiences.

Skill
7061

Skill in developing and influencing policy, plans, and strategy in compliance with laws, regulations, policies, and standards in support of organizational AI activities.

Skill
7065

Skill in explaining AI concepts and terminology.

Skill
7068

Skill in identifying organizational and project-level AI risks, including AI security risks and requirements.

Skill
7072

Skill in leading AI adoption efforts.

Skill
7073

Skill in leveraging and optimizing resources required to complete AI projects and programs.

Skill

Additional KSATs

KSAT ID Description KSAT
3146

Knowledge of both internal and external customers and partner organizations, including information needs, objectives, structure, capabilities, etc.

Knowledge
3356

Knowledge of organization policies and planning concepts for partnering with internal and/or external organizations.

Knowledge
5330A

Establish and collect metrics to monitor and validate AI workforce readiness.

Task
5868

Define and/or implement policies and procedures to enable an AI risk assessment process and assess risk mitigation efforts.

Task
5902

Monitor and evaluate the organization’s use of AI to ensure capabilities are performing as intended and to reduce the likelihood and severity of unintended consequences.

Task
5912

Recommend updates to military strategy and doctrine with respect to advances in AI technology, legal obligations, Responsible AI, and DoD AI Ethical Principles.

Task
6290

Knowledge of how to leverage government research and development centers, think tanks, academic research, and industry systems.

Knowledge
7005

Knowledge of AI-specific acquisition models (e.g., pay per use or per data element).

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7038

Knowledge of metrics to evaluate the effectiveness of machine learning models.

Knowledge
7039

Knowledge of organization’s structure, training requirements, and existing operational hardware/software related to the AI solution to be adopted.

Knowledge
7041

Knowledge of remedies against unintended bias in AI solutions.

Knowledge
7051

Knowledge of the possible impacts of machine learning blind spots and edge cases.

Knowledge
AI Risk & Ethics Specialist Work Role ID: 733 (NIST: N/A) Workforce Element: Data/AI

Educates those involved in the development of AI and conducts assessments on the technical and societal risks across the lifecycle of AI solutions from acquisition or design to deployment and use.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
537A

Develop methods to monitor and measure risk and assurance efforts on a continuous basis.

Task
765B

Perform AI architecture security reviews, identify gaps, and develop a risk management plan to address issues.

Task
952

Knowledge of emerging security issues, risks, and vulnerabilities.

Knowledge
963A

Ensure risk mitigation plans of action and milestones are in place.

Task
1000B

Ensure that AI design and development activities are properly documented and updated.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5856

Communicate the results of AI risk assessments to relevant stakeholders.

Task
5860

Coordinate with appropriate personnel to identify methods for users and developers to report concerns about the implementation of DoD AI Ethical Principles.

Task
5863

Create and/or maintain processes to ensure data management efforts comply with AI ethical principles.

Task
5873

Determine methods and metrics for quantitative and qualitative measurement of AI risks so that sensitivity, specificity, likelihood, confidence levels, and other metrics are identified, documented, and applied.

Task
5878

Develop risk mitigation strategies to ensure enumerated risks are prioritized, mitigated, shared, transferred, and/or accepted.

TAsk
5879

Direct and/or support organizational and project-level AI risk management activities.

Task
5881

Ensure risk management responsibilities are clearly defined, assigned, and communicated to relevant stakeholders.

Task
5889

Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports.

Task
5893

Implement Responsible AI best practices and standards within AI solutions according to the DoD AI Ethical Principles, Responsible AI Guidelines, and/or any other pertinent laws.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5900

Measure the compliance of AI tools with DoD AI Ethical Principles.

Task
5904

Perform risk assessment on AI applications to identify technical, societal, organizational, and mission risks.

Task
6311

Knowledge of machine learning theory and principles.

Knowledge
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7003

Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7021

Knowledge of emerging trends and future use cases of AI.

Knowledge
7024

Knowledge of how AI is developed and operated.

Knowledge
7034

Knowledge of interactions and integration of DataOps, MLOps, and DevSecOps in AI.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7038

Knowledge of metrics to evaluate the effectiveness of machine learning models.

Knowledge
7040

Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.

Knowledge
7041

Knowledge of remedies against unintended bias in AI solutions.

Knowledge
7045

Knowledge of the AI lifecycle.

Knowledge
7048

Knowledge of the benefits and limitations of AI capabilities.

Knowledge
7051

Knowledge of the possible impacts of machine learning blind spots and edge cases.

Knowledge
7052

Knowledge of the principles, methods, and tools used for risk and bias assessment and mitigation, including assessment of failures and their consequences.

Knowledge
7056

Skill in assessing AI capabilities for bias or ethical concerns.

Skill
7064

Skill in developing solutions and/or recommendations to minimize negative impacts of machine learning, especially for edge cases.

Skill
7065

Skill in explaining AI concepts and terminology.

Skill
7067

Skill in identifying low-probability, high-impact risks in machine learning training data sets.

Skill
7068

Skill in identifying organizational and project-level AI risks, including AI security risks and requirements.

Skill
7069

Skill in identifying risk over the lifespan of an AI solution.

Skill
7075

Skill in testing and evaluating machine learning algorithms or AI solutions.

Skill

Additional KSATs

KSAT ID Description KSAT
942

Knowledge of the organization’s core business/mission processes.

Knowledge
5905

Perform risk assessment whenever an AI application or AI-enabled system undergoes a major change, when emergent behaviors are detected, and/or unintended consequences are reported.

Task
7044

Knowledge of testing, evaluation, validation, and verification (T&E V&V) tools and procedures to ensure systems are working as intended.

Knowledge
AI Test & Evaluation Specialist Work Role ID: 672 (NIST: N/A) Workforce Element: Data/AI

Performs testing, evaluation, verification, and validation on AI solutions to ensure they are developed to be and remain robust, resilient, responsible, secure, and trustworthy; and communicates results and concerns to leadership.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
182

Skill in determining an appropriate level of test rigor for a given system.

Skill
508

Determine level of assurance of developed capabilities based on test results.

Task
550

Develop test plans to address specifications and requirements.

Task
694

Make recommendations based on test results.

Task
858A

Test, evaluate, and verify hardware and/or software to determine compliance with defined specifications and requirements.

Task
858B

Record and manage test data.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
5120

Conduct hypothesis testing using statistical processes.

Task
5848

Assess technical risks and limitations of planned tests on AI systems.

Task
5851

Build assurance cases for AI systems that support the needs of different stakeholders (e.g., acquisition community, commanders, and operators).

Task
5858

Conduct AI risk assessments to ensure models and/or other solutions are performing as designed.

Task
5866

Create or customize existing Test and Evaluation Master Plans (TEMPs) for AI systems.

Task
5873

Determine methods and metrics for quantitative and qualitative measurement of AI risks so that sensitivity, specificity, likelihood, confidence levels, and other metrics are identified, documented, and applied.

Task
5876

Develop machine learning code testing and validation procedures.

Task
5877

Develop possible solutions for technical risks and limitations of planned tests on AI solutions.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5901

Measure the effectiveness, security, robustness, and trustworthiness of AI tools.

Task
5910

Provide quality assurance of AI products throughout their lifecycle.

Task
5914

Report test and evaluation deficiencies and possible solutions to appropriate personnel.

Task
5916

Select and use the appropriate models and prediction methods for evaluating AI performance.

Task
5919

Test AI tools against adversarial attacks in operationally realistic environments.

Task
5920

Test components to ensure they work as intended in a variety of scenarios for all aspects of the AI application.

Task
5921

Test how users interact with AI solutions.

Task
5922

Test the reliability, functionality, security, and compatibility of AI tools within systems.

Task
5923

Test the trustworthiness of AI solutions.

Task
5926

Use models and other methods for evaluating AI performance.

Task
6060

Ability to collect, verify, and validate test data.

Ability
6170

Ability to translate data and test results into evaluative conclusions.

Ability
6311

Knowledge of machine learning theory and principles.

Knowledge
6490

Skill in assessing the predictive power and subsequent generalizability of a model.

Skill
6630

Skill in preparing Test & Evaluation reports.

Skill
6641

Skill in providing Test & Evaluation resource estimate.

Skill
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7003

Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.

Knowledge
7004

Knowledge of AI Test & Evaluation frameworks.

Knowledge
7006

Knowledge of best practices from industry and academia in test design activities for verification and validation of AI and machine learning systems.

Knowledge
7009

Knowledge of coding and scripting in languages that support AI development and use.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7024

Knowledge of how AI is developed and operated.

Knowledge
7025

Knowledge of how AI solutions integrate with cloud or other IT infrastructure.

Knowledge
7028

Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software to the DoD.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7030

Knowledge of how to deploy test infrastructures with AI systems.

Knowledge
7034

Knowledge of interactions and integration of DataOps, MLOps, and DevSecOps in AI.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7037

Knowledge of machine learning operations (MLOps) processes and best practices.

Knowledge
7038

Knowledge of metrics to evaluate the effectiveness of machine learning models.

Knowledge
7041

Knowledge of remedies against unintended bias in AI solutions.

Knowledge
7044

Knowledge of testing, evaluation, validation, and verification (T&E V&V) tools and procedures to ensure systems are working as intended.

Knowledge
7045

Knowledge of the AI lifecycle.

Knowledge
7048

Knowledge of the benefits and limitations of AI capabilities.

Knowledge
7051

Knowledge of the possible impacts of machine learning blind spots and edge cases.

Knowledge
7053

Knowledge of the user experience (e.g., decision making, user design, and human-computer interaction) as it relates to AI systems.

Knowledge
7054

Knowledge of tools for testing the robustness and resilience of AI products and solutions.

Knowledge
7065

Skill in explaining AI concepts and terminology.

Skill
7067

Skill in identifying low-probability, high-impact risks in machine learning training data sets.

Skill
7069

Skill in identifying risk over the lifespan of an AI solution.

Skill
7070

Skill in integrating AI Test & Evaluation frameworks into test strategies for specific projects.

Skill
7075

Skill in testing and evaluating machine learning algorithms or AI solutions.

Skill
7076

Skill in testing for bias in data sets and AI system outputs as well as determining historically or often underrepresented and marginalized groups are properly represented in the training, testing, and validation data sets and AI system outputs.

Skill
7077

Skill in translating operation requirements for AI systems into testing requirements.

Skill

Additional KSATs

KSAT ID Description KSAT
40

Knowledge of organization’s evaluation and validation requirements.

Knowledge
765B

Perform AI architecture security reviews, identify gaps, and develop a risk management plan to address issues.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1133

Knowledge of service management concepts for networks and related standards (e.g., Information Technology Infrastructure Library, current version [ITIL]).

Knowledge
5850

Assist integrated project teams to identify, curate, and manage data.

Task
5889

Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports.

Task
7012

Knowledge of current test standards and safety standards that are applicable to AI (e.g. MIL-STD 882E, DO-178C, ISO26262).

Knowledge
7040

Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.

Knowledge
AI/ML Specialist Work Role ID: 623 (NIST: N/A) Workforce Element: Data/AI

Designs, develops, and modifies AI applications, tools, and/or other solutions to enable successful accomplishment of mission objectives.

Core KSATs

KSAT ID Description KSAT
21

Knowledge of computer algorithms.

Knowledge
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
75A

Knowledge of mathematics, including logarithms, trigonometry, linear algebra, calculus, statistics, and operational analysis.

Knowledge
102

Knowledge of programming language structures and logic.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
166

Skill in conducting queries and developing algorithms to analyze data structures.

Skill
477

Correct errors by making appropriate changes and rechecking the program to ensure desired results are produced.

Task
506

Design, develop, and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.

Task
543

Develop secure code and error handling.

Task
764

Perform secure programming and identify potential flaws in codes to mitigate vulnerabilities.

Task
1000B

Ensure that AI design and development activities are properly documented and updated.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
5120

Conduct hypothesis testing using statistical processes.

Task
5847

Assess and address the limitations of methods to deliver machine learning models.

Task
5858

Conduct AI risk assessments to ensure models and/or other solutions are performing as designed.

Task
5871

Design and develop machine learning models to achieve organizational objectives.

Task
5872

Design, develop, and implement AI tools and techniques to achieve organizational objectives.

Task
5873

Determine methods and metrics for quantitative and qualitative measurement of AI risks so that sensitivity, specificity, likelihood, confidence levels, and other metrics are identified, documented, and applied.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5915

Research the latest machine learning and AI tools, techniques, and best practices.

Task
5926

Use models and other methods for evaluating AI performance.

Task
5927

Write and document reproducible code.

Task
6060

Ability to collect, verify, and validate test data.

Ability
6311

Knowledge of machine learning theory and principles.

Knowledge
6760

Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.

Skill
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7009

Knowledge of coding and scripting in languages that support AI development and use.

Knowledge
7011

Knowledge of current AI and machine learning systems design and performance analysis models, algorithms, and tools.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7024

Knowledge of how AI is developed and operated.

Knowledge
7028

Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software to the DoD.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7031

Knowledge of how to structure and display data.

Knowledge
7032

Knowledge of how to use data to tell a story.

Knowledge
7037

Knowledge of machine learning operations (MLOps) processes and best practices.

Knowledge
7038

Knowledge of metrics to evaluate the effectiveness of machine learning models.

Knowledge
7045

Knowledge of the AI lifecycle.

Knowledge
7046

Knowledge of the basic requirements for the successful delivery of AI solutions.

Knowledge
7048

Knowledge of the benefits and limitations of AI capabilities.

Knowledge
7049

Knowledge of the latest machine learning and AI tools, techniques, and best practices.

Knowledge
7050

Knowledge of the nature and function of technology platforms and tools used to create and employ AI.

Knowledge
7051

Knowledge of the possible impacts of machine learning blind spots and edge cases.

Knowledge
7055

Skill in analyzing the output from machine learning models.

Skill
7057

Skill in building and deploying machine learning models.

Skill
7059

Skill in creating machine learning models.

Skill
7065

Skill in explaining AI concepts and terminology.

Skill
7067

Skill in identifying low-probability, high-impact risks in machine learning training data sets.

Skill
7075

Skill in testing and evaluating machine learning algorithms or AI solutions.

Skill

Additional KSATs

KSAT ID Description KSAT
942

Knowledge of the organization’s core business/mission processes.

Knowledge
5925

Use knowledge of business processes to create or recommend AI solutions.

Task
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5859

Consider energy implications (graphical processing unit, tensor processing unit, etc.) when designing AI solutions.

Task
5870

Design and develop continuous integration/continuous delivery (CI/CD) in a containerized or other reproducible computing environment to support the machine learning life cycle.

Task
5889

Identify and submit exemplary AI use cases, best practices, failure modes, and risk mitigation strategies, including after-action reports.

Task
5893

Implement Responsible AI best practices and standards within AI solutions according to the DoD AI Ethical Principles, Responsible AI Guidelines, and/or any other pertinent laws.

Task
6290

Knowledge of how to leverage government research and development centers, think tanks, academic research, and industry systems.

Knowledge
7003

Knowledge of AI security risks, threats, and vulnerabilities and potential risk mitigation solutions.

Knowledge
7021

Knowledge of emerging trends and future use cases of AI.

Knowledge
7022

Knowledge of how AI adoption can assist developers with service-oriented design.

Knowledge
7025

Knowledge of how AI solutions integrate with cloud or other IT infrastructure.

Knowledge
7026

Knowledge of how commercial and federal solutions solve Defense-related data environment and platform challenges.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7040

Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.

Knowledge
7041

Knowledge of remedies against unintended bias in AI solutions.

Knowledge
7044

Knowledge of testing, evaluation, validation, and verification (T&E V&V) tools and procedures to ensure systems are working as intended.

Knowledge
7069

Skill in identifying risk over the lifespan of an AI solution.

Skill
7071

Skill in labeling data to make it more discoverable and understandable.

Skill
Data Analyst Work Role ID: 422 (NIST: OM-DA-002) Workforce Element: Data/AI

Analyzes and interprets data from multiple disparate sources and builds visualizations and dashboards to report insights.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
31

Knowledge of data mining and data warehousing principles.

Knowledge
104

Knowledge of query languages such as SQL (structured query language).

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
166

Skill in conducting queries and developing algorithms to analyze data structures.

Skill
201

Skill in generating queries and reports.

Skill
1120

Ability to interpret and incorporate data from multiple tool sources.

Ability
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
3022

Ability to communicate complex information, concepts, or ideas in a confident and well-organized manner through verbal, written, and/or visual means.

Ability
5030

Analyze data sources to provide actionable recommendations.

Task
5100

Collect metrics and trending data.

Task
5270

Develop strategic insights from large data sets.

Task
5430

Present technical information to technical and non-technical audiences.

Task
5899

Manipulate and clean large, disparate datasets for bulk analysis to identify connections.

Task
6130

Ability to identify basic common coding flaws at a high level.

Ability
6180

Ability to use data visualization tools (e.g., Flare, HighCharts, AmCharts, D3.js, Processing, Google Visualization API, Tableau, Raphael.js).

Ability
6300

Knowledge of how to utilize Hadoop, Java, Python, SQL, Hive, and PIG to explore data.

Knowledge
6470A

Read, interpret, write, modify, and execute scripts, macros, and functions.

Task
6570

Skill in identifying hidden patterns or relationships.

Skill
6710

Skill in using basic descriptive statistics and techniques (e.g., normality, model distribution, scatter plots).

Skill
6720

Skill in using data analysis tools (e.g., Excel, STATA SAS, SPSS).

Skill
6780

Utilize different programming languages to write code, open files, read files, and write output to different files.

Task
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7031

Knowledge of how to structure and display data.

Knowledge
7032

Knowledge of how to use data to tell a story.

Knowledge

Additional KSATs

KSAT ID Description KSAT
796

Provide a managed flow of relevant information (via web-based portals or other means) based on a mission requirements.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1034A

Knowledge of Personally Identifiable Information (PII) data security standards.

Knowledge
1034C

Knowledge of Personal Health Information (PHI) data security standards.

Knowledge
5030

Analyze data sources to provide actionable recommendations.

Task
5440

Present data in creative formats.

Task
5570

Provide actionable recommendations to critical stakeholders based on data analysis and findings.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
6915A

Skill in communicating with all levels of the organization, including senior/mid-level executives, and operational-level personnel (e.g., interpersonal skills, approachability, effective listening skills, appropriate use of style and language for the audience).

Skill
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
Data Architect Work Role ID: 653 (NIST: N/A) Workforce Element: Data/AI

Designs a system’s data models, data flow, interfaces, and infrastructure to meet the information requirements of a business or mission.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
28

Knowledge of data administration and data standardization policies and standards.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
135

Knowledge of the capabilities and functionality associated with various technologies for organizing and managing information (e.g., databases, bookmarking engines).

Knowledge
137

Knowledge of the characteristics of physical and virtual data storage media.

Knowledge
187

Skill in developing data models.

Skill
401

Analyze and plan for anticipated changes in data capacity requirements.

Task
408

Analyze information to determine, recommend, and plan the development of a new application or modification of an existing application.

Task
466A

Consult with customers and key stakeholders to evaluate functional requirements for AI and data applications.

Task
815

Provide recommendations on new database technologies and architectures.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
5140

Confer with systems analysts, engineers, programmers and others to design application.

Task
5841

Advise higher level leadership on critical data management issues.

Task
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5885

Examine and identify database structural necessities by evaluating operations, applications, and programming.

Task
5908

Prepare database design and architecture reports.

Task
6190

Effectively allocate storage capacity in the design of data management systems.

Task
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7017

Knowledge of data operations (DataOps) processes and best practices.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7060

Skill in designing the best approach and architecture for automated data labeling and data lifecycle.

Skill

Additional KSATs

KSAT ID Description KSAT
28

Knowledge of data administration and data standardization policies and standards.

Knowledge
79

Knowledge of network access, identity, and access management (e.g., public key infrastructure [PKI]).

Knowledge
296

Knowledge of how information needs and collection requirements are translated, tracked, and prioritized across the extended enterprise.

Knowledge
942

Knowledge of the organization’s core business/mission processes.

Knowledge
952

Knowledge of emerging security issues, risks, and vulnerabilities.

Knowledge
1034A

Knowledge of Personally Identifiable Information (PII) data security standards.

Knowledge
1034C

Knowledge of Personal Health Information (PHI) data security standards.

Knowledge
1133

Knowledge of service management concepts for networks and related standards (e.g., Information Technology Infrastructure Library, current version [ITIL]).

Knowledge
1141A

Knowledge of an organization’s information classification program and procedures for information compromise.

Knowledge
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
6650

Skill in developing machine understandable semantic ontologies.

Skill
7010

Knowledge of container orchestration and resource management platforms.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7025

Knowledge of how AI solutions integrate with cloud or other IT infrastructure.

Knowledge
7026

Knowledge of how commercial and federal solutions solve Defense-related data environment and platform challenges.

Knowledge
7028

Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software to the DoD.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
Data Officer Work Role ID: 903 (NIST: N/A) Workforce Element: Data/AI

Holds responsibility for developing, promoting, and overseeing implementation of data as an asset and the establishment and enforcement of data-related strategies, policies, standards, processes, and governance.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
79

Knowledge of network access, identity, and access management (e.g., public key infrastructure [PKI]).

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
120

Knowledge of sources, characteristics, and uses of the organization’s data assets.

Knowledge
296

Knowledge of how information needs and collection requirements are translated, tracked, and prioritized across the extended enterprise.

Knowledge
524

Develop and maintain strategic plans.

Task
529

Develop data standards, policies, and procedures.

Task
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
2416

Facilitate interactions between internal and external partner decision makers to synchronize and integrate courses of action in support of objectives.

Task
3591

Knowledge of organization objectives, leadership priorities, and decision-making risks.

Knowledge
5841

Advise higher level leadership on critical data management issues.

Task
5842

Analyze existing and planned data investments to ensure they address key business problems, are compatible with the organization’s mission, and align with the target data architecture.

Task
5867

Create policies for effective data management (e.g., data sharing agreements and security policies).

Task
5869

Demonstrate to executive stakeholders how data and analytics initiatives address agency challenges.

Task
5874

Develop a data management strategy that helps to prioritize investments and resource allocations (e.g., data analytics, data infrastructure).

Task
5875

Develop an organizational change management plan to support a data management strategy.

Task
5886

Facilitate cross-sharing of best practices for data usage.

Task
5894

Lead the development and documentation of solutions for assigned data analytical objectives and projects.

Task
5895

Lead the improvement of data system design processes that affect the success and continuation of key programs.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5898

Manage risk to the data program.

Task
5903

Oversee the management of data classification and handling requirements.

Task
5913

Remove barriers to data acquisition, collection, and curation efforts required for AI solutions.

Task
5917

Set strategic priorities by leveraging data insights.

Task
6040

Ability to assess and forecast manpower requirements to meet organizational objectives.

Ability
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6915A

Skill in communicating with all levels of the organization, including senior/mid-level executives, and operational-level personnel (e.g., interpersonal skills, approachability, effective listening skills, appropriate use of style and language for the audience).

Skill
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7001

Ability to inspire and lead a culture of innovation.

Ability
7014

Knowledge of data acquisition, collection, and curation best practices required for AI solutions.

Knowledge
7015

Knowledge of data architecture and data services implementation.

Knowledge
7016

Knowledge of data model development (e.g., conceptual, logical, and physical).

Knowledge
7019

Knowledge of data security roles and responsibilities.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7063

Skill in developing enterprise-level/Agency-level policies.

Skill
7074

Skill in performing strategic-level analysis to develop Enterprise Data Management (EDM) strategies.

Skill
7083

Ability to understand technology, management, and leadership issues related to organization processes and problem solving.

Ability
7110

Ability to understand technology, management, and leadership issues related to organization processes and problem solving.

Ability

Additional KSATs

KSAT ID Description KSAT
559C

Oversee the evaluation of contracts to ensure compliance with funding, legal, and program requirements.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1018

Ensure all acquisitions, procurements, and outsourcing efforts address information security requirements consistent with organization goals.

Task
2558

Maintain relationships with internal and external partners involved in cyber planning or related areas.

Task
3146

Knowledge of both internal and external customers and partner organizations, including information needs, objectives, structure, capabilities, etc.

Knowledge
3356

Knowledge of organization policies and planning concepts for partnering with internal and/or external organizations.

Knowledge
6250

Knowledge of Workforce Framework, work roles, and associated tasks, knowledge, skills, and abilities.

Knowledge
6290

Knowledge of how to leverage government research and development centers, think tanks, academic research, and industry systems.

Knowledge
Data Operations Specialist Work Role ID: 624 (NIST: N/A) Workforce Element: Data/AI

Builds, manages, and operationalizes data pipelines.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
28

Knowledge of data administration and data standardization policies and standards.

Knowledge
31

Knowledge of data mining and data warehousing principles.

Knowledge
32

Knowledge of database management systems, query languages, table relationships, and views.

Knowledge
104

Knowledge of query languages such as SQL (structured query language).

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
179B

Skill in establishing data security controls.

Skill
186

Skill in developing data dictionaries.

Skill
400A

Implement data management standards, requirements, and specifications.

Task
520B

Develop and implement data mining and data warehousing programs.

Task
543

Develop secure code and error handling.

Task
702

Manage the compilation, cataloging, caching, distribution, and retrieval of data.

Task
764

Perform secure programming and identify potential flaws in codes to mitigate vulnerabilities.

Task
858B

Record and manage test data.

Task
1128

Knowledge of Java-based database access application programming interface (API) (e.g., Java Database Connectivity [JDBC]).

Knowledge
1128A

Knowledge of database access application programming interfaces (APIs) (e.g., Java Database Connectivity [JDBC]).

Knowledge
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
3722

Skill in data mining techniques (e.g., searching file systems) and analysis.

Skill
5550

Program custom algorithms.

Task
5841

Advise higher level leadership on critical data management issues.

Task
5844

Apply data acquisition, cleaning, transformation, and ingestion best practices for machine learning data conduits.

Task
5846

Assess and address the limitations of methods to deliver data.

Task
5850

Assist integrated project teams to identify, curate, and manage data.

Task
5852

Build automated data management conduits.

Task
5857

Comply with data classification and handling requirements through access control and security best practices.

Task
5899

Manipulate and clean large, disparate datasets for bulk analysis to identify connections.

Task
6060

Ability to collect, verify, and validate test data.

Ability
6300

Knowledge of how to utilize Hadoop, Java, Python, SQL, Hive, and PIG to explore data.

Knowledge
6470

Read, interpret, write, modify, and execute simple scripts (e.g., PERL, VBS) on Windows and UNIX systems (e.g., those that perform tasks such as: parsing large data files, automating manual tasks, and fetching/processing remote data).

Task
6520

Skill in data pre-processing (e.g., imputation, dimensionality reduction, normalization, transformation, extraction, filtering, smoothing).

Skill
6610

Skill in performing format conversions to create a standard representation of the data.

Skill
6690

Skill in transformation analytics (e.g., aggregation, enrichment, processing).

Skill
6730

Skill in using data mapping tools.

Skill
6760

Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.

Skill
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7017

Knowledge of data operations (DataOps) processes and best practices.

Knowledge
7019

Knowledge of data security roles and responsibilities.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7062

Skill in developing and maintaining automation scripts.

Skill
7066

Skill in identifying data acquisition, collection, and curation risks.

Skill

Additional KSATs

KSAT ID Description KSAT
520A

Implement data mining and data warehousing applications.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1034A

Knowledge of Personally Identifiable Information (PII) data security standards.

Knowledge
1034C

Knowledge of Personal Health Information (PHI) data security standards.

Knowledge
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
7010

Knowledge of container orchestration and resource management platforms.

Knowledge
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7025

Knowledge of how AI solutions integrate with cloud or other IT infrastructure.

Knowledge
7028

Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software to the DoD.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
Data Scientist Work Role ID: 423 (NIST: N/A) Workforce Element: Data/AI

Uncovers and explains actionable insights from data by combining scientific method, math and statistics, specialized programming, advanced analytics, AI, and storytelling.

Core KSATs

KSAT ID Description KSAT
21A

Knowledge of statistical/machine learning algorithms.

Knowledge
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
75A

Knowledge of mathematics, including logarithms, trigonometry, linear algebra, calculus, statistics, and operational analysis.

Knowledge
102

Knowledge of programming language structures and logic.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
166

Skill in conducting queries and developing algorithms to analyze data structures.

Skill
172

Skill in creating and utilizing mathematical or statistical models.

Skill
1120

Ability to interpret and incorporate data from multiple tool sources.

Ability
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
3080

Ability to use and understand complex mathematical concepts (e.g., discrete math).

Ability
3756

Skill in developing or recommending analytic approaches or solutions to problems and situations for which information is incomplete or for which no precedent exists.

Skill
5030

Analyze data sources to provide actionable recommendations.

Task
5120

Conduct hypothesis testing using statistical processes.

Task
5550

Program custom algorithms.

Task
5640

Utilize technical documentation or resources to implement a new mathematical, data science, or computer science method.

Task
5853

Build predictive, prescriptive, or descriptive models in collaboration with stakeholders.

Task
5906

Plan and conduct complex analytical, mathematical, and statistical research that informs operational requirements.

Task
5907

Plan, coordinate, and execute complex studies using advanced data modeling techniques and procedures, data trend analysis, and data algorithms.

Task
5924

Train and evaluate machine learning models.

Task
5927

Write and document reproducible code.

Task
6050

Ability to build complex data structures and high-level programming languages.

Ability
6060

Ability to collect, verify, and validate test data.

Ability
6120

Ability to dissect a problem and examine the interrelationships between data that may appear unrelated.

Ability
6490

Skill in assessing the predictive power and subsequent generalizability of a model.

Skill
6570

Skill in identifying hidden patterns or relationships.

Skill
6651

Skill in Regression Analysis (e.g., Hierarchical Stepwise, Generalized Linear Model, Ordinary Least Squares, Tree-Based Methods, Logistic).

Skill
6750

Skill in using outlier identification and removal techniques.

Skill
6760

Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.

Skill
6790A

Utilize open source languages, as appropriate, and apply quantitative techniques (e.g., descriptive and inferential statistics, sampling, experimental design, parametric and non-parametric tests of difference, ordinary least squares regression, general line).

Task
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7002

Assist integrated project teams identify, curate, and manage test data.

Task
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7071

Skill in labeling data to make it more discoverable and understandable.

Skill

Additional KSATs

KSAT ID Description KSAT
35

Knowledge of digital rights management.

Knowledge
506

Design, develop, and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
1034A

Knowledge of Personally Identifiable Information (PII) data security standards.

Knowledge
1034C

Knowledge of Personal Health Information (PHI) data security standards.

Knowledge
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5884

Evaluate energy implications (graphical processing unit, tensor processing unit, etc.) when designing AI solutions.

Task
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
5907

Plan, coordinate, and execute complex studies using advanced data modeling techniques and procedures, data trend analysis, and data algorithms.

Task
6290

Knowledge of how to leverage government research and development centers, think tanks, academic research, and industry systems.

Knowledge
6651

Skill in Regression Analysis (e.g., Hierarchical Stepwise, Generalized Linear Model, Ordinary Least Squares, Tree-Based Methods, Logistic).

Skill
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7078

Skill in using deep learning approaches to build machine learning models.

Skill
Data Steward Work Role ID: 424 (NIST: N/A) Workforce Element: Data/AI

Develops and maintains plans, policies, and processes for data management, data governance, security, quality, accessibility, use, and disposal.

Core KSATs

KSAT ID Description KSAT
22

* Knowledge of computer networking concepts and protocols, and network security methodologies.

Knowledge
28

Knowledge of data administration and data standardization policies and standards.

Knowledge
108

* Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).

Knowledge
186

Skill in developing data dictionaries.

Skill
400A

Implement data management standards, requirements, and specifications.

Task
400

Analyze and define data requirements and specifications.

Task
702

Manage the compilation, cataloging, caching, distribution, and retrieval of data.

Task
918

Ability to prepare and deliver education and awareness briefings to ensure that systems, network, and data users are aware of and adhere to systems security policies and procedures.

Ability
1034A

Knowledge of Personally Identifiable Information (PII) data security standards.

Knowledge
1034C

Knowledge of Personal Health Information (PHI) data security standards.

Knowledge
1157

* Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.

Knowledge
1158

* Knowledge of cybersecurity principles.

Knowledge
1159

* Knowledge of cyber threats and vulnerabilities.

Knowledge
5080

Assess the validity of source data and subsequent findings.

Task
5380A

Review feedback on customer satisfaction and internal service performance to foster continual improvement.

Task
5850

Assist integrated project teams to identify, curate, and manage data.

Task
5854

Collaborate with appropriate personnel to address Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data resusability concerns for AI solutions.

Task
5855

Collaborate with data owners to establish data quality rules and definitions.

Task
5864

Create data catalogs and dictionaries.

Task
5865

Create metrics that characterize the usability, timeliness, completeness, and accuracy of data for multiple users to reference and use.

Task
5888

Identify and document customer requirements when on-boarding new data assets.

Task
5897

Manage compliance with data classification and handling requirements.

Task
5911

Recommend data collection, integration, and retention requirements.

Task
6060

Ability to collect, verify, and validate test data.

Ability
6900

* Knowledge of specific operational impacts of cybersecurity lapses.

Knowledge
6915A

Skill in communicating with all levels of the organization, including senior/mid-level executives, and operational-level personnel (e.g., interpersonal skills, approachability, effective listening skills, appropriate use of style and language for the audience).

Skill
6935

* Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).

Knowledge
6938

* Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Knowledge
7018

Knowledge of data protection standards and frameworks to prevent unauthorized access to data, and safeguard against unauthorized disclosure of data.

Knowledge
7019

Knowledge of data security roles and responsibilities.

Knowledge
7029

Knowledge of how to collect, store, and monitor data.

Knowledge
7036

Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.

Knowledge
7040

Knowledge of Personal Health Information (PHI), Personally Identifiable Information (PII), and other data privacy and data reusability considerations for AI solutions.

Knowledge
7071

Skill in labeling data to make it more discoverable and understandable.

Skill

Additional KSATs

KSAT ID Description KSAT
296

Knowledge of how information needs and collection requirements are translated, tracked, and prioritized across the extended enterprise.

Knowledge
466A

Consult with customers and key stakeholders to evaluate functional requirements for AI and data applications.

Task
942

Knowledge of the organization’s core business/mission processes.

Knowledge
5896

Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.

Task
6650

Skill in developing machine understandable semantic ontologies.

Skill
7020

Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).

Knowledge
7035

Knowledge of key decision-support needs and questions to drive prioritization of data efforts.

Knowledge