Senior Data Scientist

Diné Development Corporation

32d

About The Position

The Senior Data Scientist – Model Governance & DoD Data Fabrics leads the full lifecycle of advanced analytics and machine learning models in support of a Department of Defense (DoD) customer. In this role, you will own model development, deployment, monitoring, and governance across DoD data fabrics, with a strong emphasis on causal inference, Bayesian methods, model risk management, model cards, and ethical AI practices. You will ensure all models and analytics products align with the contract’s Acceptable Quality Levels (AQLs) and Quality Assurance Surveillance Plan (QASP), providing decision-quality insights to senior government stakeholders while maintaining rigorous technical and compliance standards. This position is contingent upon contract award.

Requirements

• Clearance: Active Secret clearance; must be able to obtain and maintain a Top Secret clearance if required by the customer. U.S. citizenship is required due to government contract requirements.
• Experience: 9–12 years of progressive experience in data science, machine learning, statistics, or a closely related field, including support to DoD or other U.S. government customers.
• Education: Master’s degree (MS) in Data Science, Computer Science, Statistics, Electrical Engineering, or a closely related discipline (required). PhD in one of these fields (preferred).
• Demonstrated hands-on expertise with causal inference and Bayesian methods applied to real-world decision problems.
• Proven experience implementing and maintaining model risk management frameworks in production environments.
• Experience generating model cards and other structured documentation for models, including performance metrics and limitations.
• Strong background in ethical AI concepts and techniques, including bias detection/mitigation and responsible AI governance.
• Hands-on experience deploying and scaling models on cloud platforms and/or DoD data fabrics (e.g., enterprise data platforms, secure enclaves).
• Proficiency in at least one major programming language used for data science (e.g., Python, R) and modern ML tooling (e.g., scikit-learn, PyTorch, TensorFlow).
• Strong communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.

Nice To Haves

• Relevant cloud architect or ML specialty certification (e.g., AWS, Azure, or other major cloud provider).
• CompTIA Security+ certification.
• ITIL Foundation certification (preferred).
• Experience working with QASP-driven contracts and defining/monitoring AQLs for analytics or IT services.
• Familiarity with DoD cybersecurity frameworks, RMF, and secure DevSecOps practices.
• Prior experience supporting Air Force, joint, or combatant command–level analytics, or similar high-visibility federal programs.

Responsibilities

• Lead the end-to-end lifecycle of machine learning and statistical models, from problem framing and data acquisition through deployment, monitoring, and retirement.
• Design and implement models using causal inference and Bayesian methods to support high-impact operational and strategic decisions.
• Develop and maintain model risk management practices, including validation, back-testing, performance thresholds, and issue remediation.
• Create and maintain model cards and other documentation that clearly describe model purpose, assumptions, limitations, performance, and governance controls.
• Embed ethical AI principles into model design and usage, including fairness, transparency, clarity, and human-in-the-loop oversight.
• Architect and scale analytical solutions on DoD data fabrics and cloud environments, collaborating with cloud architects and engineering teams.
• Define and track model and analytics performance against AQLs and QASP metrics; proactively recommend improvements to meet or exceed targets.
• Partner with security, infrastructure, and operations teams to ensure models comply with cybersecurity, data protection, and configuration management policies.
• Provide technical leadership and mentorship to junior data scientists and analysts, reviewing work products and promoting best practices.
• Prepare and deliver briefings, dashboards, and written reports that distill complex analytics into clear, actionable insights for senior leaders.
• Support proposal and capture efforts by contributing data science subject matter expertise and solution concepts as needed.
• Performs other related duties as assigned.

Benefits

• Eligible full-time employees receive a comprehensive benefits package, including medical, dental, vision, life and disability coverage, retirement savings with company match, paid time off, voluntary supplemental benefits, and access to an employee assistance program.
• The package also includes educational assistance, with tuition reimbursement.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level