Sr Data Scientist

Posted Yesterday
Hiring Remotely in US
Remote
Senior level
Healthtech • Information Technology • Consulting
The Role
Leads technical support for VA healthcare AI citizen developers, developing and validating supervised, unsupervised, and reinforcement learning models. Builds synthetic healthcare data cohorts, designs secure cloud-based data science workflows, collaborates with federal stakeholders, interprets analytical results, mentors developers, and ensures model quality, documentation, privacy, governance, and regulatory compliance.
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Job Summary

Job Title: Data Scientist Sr


As a Senior Data Scientist supporting the VA's AI Citizen Developer Ecosystem (TOPR 0049), you will lead technical support activities that empower Veterans Health Administration (VHA) staff to leverage artificial intelligence and machine learning solutions across clinical and operational domains. Working within a cutting-edge federal healthcare environment, you will apply advanced ML techniques—spanning supervised, unsupervised, and reinforcement learning—to develop, validate, and analyze healthcare-specific data models and synthetic data cohorts that drive meaningful outcomes for Veterans. This role sits at the intersection of data science innovation and mission-driven public service, contributing directly to the VA's strategic goal of becoming an AI-enabled enterprise.


The ideal candidate is a self-directed, collaborative problem-solver who thrives in complex, matrixed federal environments and can translate sophisticated data science concepts into actionable insights for both technical and non-technical stakeholders. You bring deep intellectual curiosity about healthcare data, a commitment to responsible AI practices, and the ability to mentor and guide citizen developers as they build and scale AI solutions.


Primary Responsibilities

JOB DUTIES.

  • Lead technical support and advisory services for VHA AI Citizen Developers, guiding the design, development, and deployment of machine learning models and AI-driven solutions within the Veterans Health Administration ecosystem.
  • Apply supervised, unsupervised, and reinforcement learning techniques to build and validate predictive models and analytical pipelines tailored to healthcare-specific use cases, including clinical decision support and population health management.
  • Develop, maintain, and analyze synthetic data models and cohorts that protect Veteran data privacy while enabling robust model training, testing, and validation activities across VHA programs.
  • Architect and execute data science workflows within cloud-based analytic environments (e.g., AWS GovCloud, Microsoft Azure Government), ensuring scalability, security compliance, and alignment with VA data governance standards.
  • Collaborate with cross-functional teams—including VHA program offices, data engineers, and IT stakeholders—to define requirements, interpret analytical results, and translate findings into strategic recommendations that support AI/ML project objectives.
  • Contribute to the documentation, peer review, and continuous improvement of AI/ML methodologies, model performance metrics, and data quality standards, ensuring solutions meet federal regulatory requirements and VA enterprise AI policies.
Minimum Qualifications

MINIMUM QUALIFICATIONS.

  • Minimum 8 years of hands-on experience in data science, applied machine learning, or a closely related quantitative discipline, with demonstrated expertise in healthcare or life sciences data environments.
  • Master's Degree (required) in Statistics, Mathematics, Computer Science, Data Science, or a related field from an accredited institution; PhD preferred.
  • Previous experience working with federal agencies, preferably the Department of Veterans Affairs (VA) or other federal healthcare clients such as CMS, NIH, DoD, or HHS, with familiarity of federal data governance and compliance frameworks.
  • Ability to obtain and maintain a VA Position of Public Trust (Medium Background Investigation) or equivalent federal security clearance as required by the contract; active clearance or PIV eligibility preferred.
  • Must be authorized to work in the United States; this position does not offer visa sponsorship.
  • Demonstrated experience developing and analyzing healthcare-specific data models and patient cohorts, including familiarity with clinical data standards such as HL7 FHIR, ICD-10, CPT coding, and EHR-sourced datasets.
About Aptive

About Aptive. Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.

EEO Statement

Aptive is an equal opportunity employer. We consider all qualified applicants for employment without regard to race, color, national origin, religion, creed, sex, sexual orientation, gender identity, marital status, parental status, veteran status, age, disability, or any other protected class. Veterans, members of the Reserve and National Guard, and transitioning active-duty service members are highly encouraged to apply. About Aptive: Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.

Skills Required

  • At least 8 years of hands-on experience in data science, applied machine learning, or a closely related quantitative discipline
  • Experience in healthcare or life sciences data environments
  • Master's degree in Statistics, Mathematics, Computer Science, Data Science, or a related field from an accredited institution
  • Experience working with federal agencies, preferably the Department of Veterans Affairs or federal healthcare clients
  • Familiarity with federal data governance and compliance frameworks
  • Ability to obtain and maintain a VA Position of Public Trust or equivalent federal security clearance
  • Authorization to work in the United States
  • Experience developing and analyzing healthcare-specific data models and patient cohorts
  • Familiarity with HL7 FHIR, ICD-10, CPT coding, and EHR-sourced datasets
  • PhD
  • Active clearance or PIV eligibility
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The Company
HQ: Alexandria, VA
349 Employees
Year Founded: 2012

What We Do

Led by CEO Rachele Cooper, a Navy Veteran and aerospace engineer, Aptive is a trusted partner and consulting services provider for federal organizations seeking to accomplish strategic transformations, improve performance and leverage modern technology. Aptive is an ISO 9001:2015 and CMMI L3 certified business and has supported the federal government for more than a decade across a range of high-profile programs. We provide our clients with program and project management, strategy, analysis, integration and implementation across an array of services, including: *Health Care Innovation *Digital and Technology Solutions *Strategic Communications and Marketing Aptive is a Service Disabled Veteran Owned Small Business (SDVOSB) and Woman Owned Small Business (WOSB) headquartered in Alexandria, Virginia. ∙ 2021 Top Workplace (The Washington Post) ∙ 2021 Best Places to Work in Virginia (Virginia Business) ∙ 2020 Small Business Government Contractor of the Year (Northern Virginia Chamber of Commerce) ∙ 2020 Best Places to Work (Washington Business Journal) ∙ 2020 Vet100 Honoree – Institute for Veterans and Families

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