Senior Data Scientist

Job Summary

Aptive Resources is seeking a Senior Data Scientist with a degree in statistics, mathematics, computer science, or a related discipline and demonstrated experience applying machine learning technologies to healthcare data. In this role you will do the analytic work behind VHA’s AI oversight decisions, building the methodology that assigns risk levels to AI systems across the enterprise, evaluating whether deployed AI is delivering the benefit it promised, and providing technical consultation to field teams building AI solutions for Veteran care. This senior level, full-time position is remote. This is a contingent hire position.
Primary Responsibilities

- Design and execute the AI risk stratification pilot, developing and evaluating a new methodology for assigning risk levels to AI systems across the VHA enterprise.

- Design evaluation methodology for deployed AI systems, covering model performance, bias and fairness, construct validity, and post-deployment monitoring.

- Build and validate preregistered cost-benefit formulations that let VHA demonstrate concrete, measurable value from deployed AI systems.

- Provide technical consultation to five field pilot partnerships on model selection, data readiness, cohort construction, and evaluation design.

- Conduct the quantitative assessment of pilot outcomes supporting the program evaluation deliverable.

- Support AI oversight evaluations with analytic evidence, participating in working sessions with VHA governance entities at a cadence of at least one session every other month.

- Contribute analytic content to AI risk management playbooks, assessment guides, and training materials for use case owners and oversight personnel.

- Assess a variety of AI/ML solution approaches such as supervised, unsupervised, and reinforcing learning against specific VHA use cases and constraints.

- Develop and analyze data models and cohorts specific to the healthcare field, and advise on data quality, cohort definition, and synthetic data approaches for AI development in a protected health information environment.

Minimum Qualifications

-
Years of experience: 8 years minimum of applied data science experience. Preferred: ten or more years, including five or more designing and evaluating machine learning models on health or health-adjacent data.

-
Required experience: Previous experience applying various machine learning technologies including supervised, unsupervised, and reinforcing learning techniques. Previous experience working with cloud-based analytic environments. Previous experience working with synthetic data models and cohorts. Previous experience developing and analyzing data models and cohorts specific to the healthcare field.

-
Degree: Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related field. PhD preferred.

-
Licensure/certifications: None required.

-
Work location: Remote. Work is performed at the contractor’s site and no travel is anticipated.

-
Clearance: None required. Must be able to obtain and maintain a favorably adjudicated Tier 1 / National Agency Check with Written Inquiries (NACI) background investigation in accordance with VA Handbook 0710. Must complete VA Privacy and Information Security Awareness and Rules of Behavior training (TMS #10176) prior to system access and annually thereafter.

-
Citizenship: Must be authorized to work in the United States. All work must be performed within a jurisdiction subject to the law of the United States or its territories.

Desired Qualifications

- Demonstrated command of supervised, unsupervised, and reinforcing learning techniques and of when each is and is not appropriate.

- Experience working in cloud-based analytic environments and with synthetic data models and cohorts.

- Experience developing and analyzing data models and cohorts specific to the healthcare field.

- Familiarity with healthcare operations and clinical workflow, and the ability t