Lead efforts to extract insights from operational, service, and performance data to identify opportunities for improvement.
Lead development and deployment of advanced statistical models, machine learning algorithms, and predictive analytics solutions.
Design and develop predictive models and data-driven analytical frameworks that optimize processes and support informed decision-making.
Build models that forecast future demands, highlight operational and service-related risks, and detect performance anomalies in real time.
Collaborate with engineering and functional teams to ensure analytical outputs are accurate, actionable, and aligned with mission objectives.
Design experiments, feature engineering strategies, and model validation frameworks to support enterprise analytics objectives.
Collaborate with data engineering teams to ensure scalable data pipelines supporting model training and inference.
Integrate models into DevSecOps pipelines for automated testing, validation, and production deployment.
Develop and maintain documentation, evaluation metrics, and model performance dashboards.
Ensure responsible AI practices including bias detection, explainability, and performance monitoring.
Participate in PI Planning, backlog refinement, sprint reviews, and Inspect & Adapt events to align analytics priorities with Program Increment (PI) objectives.
Translate complex analytical findings into actionable insights for technical and executive stakeholders.
Provide direct supervision, mentoring, and performance management for assigned data scientists and analytics personnel.
Conduct performance evaluations, goal setting, and professional development planning.
Lead workforce planning and staffing alignment across data science workstreams.
Establish modeling standards, peer review processes, and analytical quality governance frameworks.
Foster a collaborative, innovative, and mission-focused analytics culture within the organization.

Requirements

Active Top Secret (TS) clearance with SCI eligibility.
Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or related technical discipline and 8 years of relevant experience OR Master’s degree in a related field and 6 years of relevant experience.
Minimum of 8 years of experience in data science, data engineering, or a related field.
Strong proficiency in programming languages such as Python, R, SQL or similar analytical programming languages.
Experience with data engineering tools and platforms, such as Hadoop, Spark, or similar.
Experience developing and deploying machine learning and statistical models in enterprise environments.
Proven experience in designing and developing predictive models and data-driven analytical frameworks.
Experience performing data exploration, feature engineering, model validation, and performance tuning.
Knowledge of data security policies, including data encryption and access controls.
Experience with data governance frameworks and compliance enforcement.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Demonstrated experience leading and mentoring technical analytics teams.

Benefits

Health and Wellness programs
Income Protection
Paid Leave
Retirement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonRSQLmachine learningstatistical modelspredictive analyticsdata explorationfeature engineeringmodel validationperformance tuning

Soft Skills

analytical skillsproblem-solving skillscommunication skillscollaboration skillsmentoringleadershipperformance managementgoal settingprofessional developmentinnovation

Certifications

Top Secret (TS) clearanceSCI eligibility