Data Scientist / Machine Learning Engineer
The Senior Data Scientist / Machine Learning Engineer will lead the development and deployment of advanced predictive models and machine learning workflows to modernize Confidential Client's GENESIS sampling and survey platform. This role involves integrating AI/ML solutions within a cloud-based Lakehouse architecture, optimizing statistical processes, and ensuring data governance and model fairness in a highly regulated federal environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT Services and IT Consulting.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Overview
Confidential Client is seeking a Senior Data Scientist / Machine Learning Engineer to support modernization of a large-scale sampling and survey management platform (GENESIS). You will develop and deploy reproducible ML workflows, optimize sampling and predictive models, and integrate solutions into a Lakehouse/cloud ecosystem. This is a remote-capable role supporting the client in Chantilly, VA (telework expected). Contract: 24 months. Pay rate: $72.00–$77.35/hr (refer to Compensation).
What You’ll Do
- Develop predictive models to improve survey sampling, response prediction, and statistical estimators.
- Perform feature engineering, algorithm selection, hyperparameter tuning, and model optimization.
- Design, train, validate, and productionize supervised ML models.
- Build reproducible ML pipelines and integrate them into the Lakehouse architecture.
- Validate model performance using A/B testing, holdout evaluation, and other statistical techniques.
- Apply FAIR data principles and data governance practices throughout the model lifecycle.
- Identify, evaluate, and mitigate model bias and fairness concerns.
- Collaborate with engineers, architects, statisticians, data specialists, and SMEs to align models with program goals.
- Document model design, assumptions, testing, and monitoring plans.
- Support automated, monitored, and well-documented data and ML pipelines.
- Contribute to testing, validation, and knowledge transfer activities.
Minimum Qualifications
- 5+ years of professional experience developing and deploying AI/ML solutions.
- Proven proficiency in Python and SQL.
- Experience with major ML frameworks (one or more): TensorFlow, PyTorch, scikit-learn.
- Hands-on experience with supervised ML, feature engineering, algorithm tuning, and model validation.
- Experience building reproducible ML pipelines and working with Lakehouse architectures (Databricks or similar).
- Familiarity with cloud platforms (preferred: Microsoft Azure).
- Understanding of data governance best practices and experience applying them in projects.
- Demonstrated ability to document methodology, testing, and results for technical and non-technical stakeholders.
Preferred Qualifications
- Prior experience supporting USDA, NASS, or other federal statistical/data programs.
- Experience on federal government technology or regulated-data projects.
- Familiarity with large-scale survey or sampling systems and statistical workflows (Python, R, SAS).
- Experience with Databricks, Azure-based data & AI environments, and reproducible analytical environments in sensitive-data contexts.
Compensation & Contract
- Pay Rate: $72.00 — $77.35 per hour (hourly contract rate).
- Contract Duration: 24 months. Note: Pay details are provided as listed by the hiring client. Applicable pay transparency laws will be respected for the posting state (Virginia).
Security & Eligibility Requirements
- This role supports systems that may contain sensitive Personally Identifiable Information (PII).
- Candidates must be U.S. Citizens or Lawful Permanent Residents.
- Successful completion of USDA-required fingerprinting and background investigation is required.
- Minimum personnel security requirement: National Agency Check with Inquiries (NACI). Additional investigation or clearance requirements may apply based on position sensitivity.
- Reasonable accommodations are available during the hiring process — applicants may request accommodations as needed.
Work Arrangement
- Job location (authoritative): Chantilly, VA (role is telecommute-eligible / remote-supporting).
- The position supports work for the client in the Chantilly, VA / Washington, DC area; regular remote work is expected while supporting program needs.
Keywords & Technologies (for applicants)
- Python, SQL
- TensorFlow, PyTorch, scikit-learn
- Lakehouse (Databricks), Azure
- Feature engineering, model validation, A/B testing
- Reproducible ML pipelines, data governance, FAIR principles
- Survey sampling, statistical workflows
About the Opportunity (brief)
This is an opportunity to deliver high-impact ML solutions within a mission-driven, highly regulated data environment. You will help modernize core sampling systems, build rigorous, reproducible analytics, and work alongside statisticians and engineers to move legacy systems to a cloud-ready architecture.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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