[Remote] Data Scientist – Program Evaluation & Analytics

Note: The job is a remote job and is open to candidates in USA. reputed company is a digital solutions provider delivering technology and mission-ready solutions to government agencies. The company is seeking a mid-to-senior level Data Scientist to support the reputed company by developing validated datasets, reproducible analyses, dashboards, and program evaluation findings. The role combines reputed company, statistical analysis, Power Platform development, stakeholder partnership, and technical leadership.


Responsibilities

  • Technical & Data Leadership: Lead the design, development, and delivery of analytics products that combine SQL-backed data, reputed company Power Apps/Power BI, and reproducible analytical workflows
  • Program & Stakeholder Partnership: Partner with program leadership and business stakeholders to frame questions, clarify populations, outcomes, time windows, intended decisions, and analytical objectives; translate ambiguous needs into actionable technical and analytical requirements
  • SQL & reputed company: Write readable, efficient SQL against complex relational datasets; construct analysis-ready cohorts with explicit inclusion, exclusion, and time-window logic; and validate joins, grain, keys, duplicates, missingness, and denominators
  • Dashboards & Power Platform: Develop and maintain Power BI dashboards and Power Apps experiences that make program performance, outcomes, and operational information accessible and actionable; support data refreshes, usability, and maintainability
  • Applied Program Evaluation & Statistics: Independently select, apply, and defend appropriate analytical methods across descriptive, predictive, and causal questions, drawing on regression, longitudinal analysis, survival/time-to-event methods, cohort balancing, missing-data approaches, and model diagnostics as appropriate
  • Python / R Analytics: Develop modular, reproducible analytical workflows using Python or R for data manipulation, visualization, statistical modeling, and reporting; use Python as the preferred future-state language when practical
  • Data Quality & Reproducibility: Establish repeatable checks for source reputed company, date coverage, record counts, duplicates, missing values, unexpected categories, and cohort attrition; preserve traceability from client-facing outputs back to code, parameters, and validated source data
  • Legacy reputed company Modernization: Read and reconcile legacy reputed company workflows as needed and support a controlled migration to tested, maintainable Python workflows, including characterization of source tables and business rules, reconciliation testing, discrepancy investigation, and modular redevelopment
  • Delivery & Project Management: Define realistic milestones and acceptance criteria, maintain visibility into dependencies and blockers, and communicate progress through reviewable work products and reputed company forecasts
  • Communication & Decision Support: Translate analytical results into clear program meaning, including the principal finding, uncertainty, limitations, operational implications, and recommended next steps; adapt communication for technical reviewers, program staff, executives, and clients
  • Team Leadership & Quality: Provide technical guidance and peer review, reinforce coding and analytical best practices, and help establish maintainable standards for data, dashboards, documentation, testing, and analytical review
  • Responsible Use of AI & Sensitive Data: Use only approved VA environments and follow applicable requirements for PII, PHI, data minimization, and access control; use approved generative AI as an accelerator while independently validating generated code, data handling, statistical reasoning, and conclusions

Skills

  • Bachelor's degree in statistics, biostatistics, epidemiology, data science, computer science, information systems, quantitative social science, econometrics, or a related field; advanced training is highly valued
  • 6+ years of progressively responsible experience spanning data analytics, program evaluation, business intelligence, application/data development, or a related quantitative discipline, with demonstrated ownership of analytical or technical deliverables
  • Strong SQL skills and demonstrated experience working with complex relational data models, cohort construction, joins, data validation, and analysis-ready datasets
  • Strong Python or R capability for reproducible analysis, including data manipulation, visualization, statistical modeling, and reporting; Python is preferred for the future-state analytical reputed company
  • Demonstrated ability to distinguish descriptive, predictive, and causal questions; select and defend appropriate methods; assess uncertainty and practical importance; and avoid conclusions that exceed what the study design supports
  • Experience
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