Dataverse, Data Science Lead

This is a fully remote position, open to applicants in District of Columbia, +1 more state.

📋 Description

• Oversee the analytical strategy for intricate operational, workflow, technology, and programmatic inquiries.

• Act as a subject-matter authority on Microsoft Dataverse data configurations, management practices, analytical applications, and integrations.

• Evaluate data readiness, quality, completeness, sensitivity, lineage, authoritative sources, access, and suitability for intended measures.

• Create and sustain reporting-ready Dataverse data models, tables, relationships, transformations, validation rules, business logic, and analytical pipelines.

• Design, review, and implement statistical models, machine-learning techniques, exploratory analyses, predictive analytics, and AI/LLM assessments.

• Conduct hands-on analysis utilizing Python, SQL, Dataverse queries, and related tools.

• Collaborate with program, operational, technical, evaluation, and data-governance stakeholders on analytical foundations and evidence limitations.

• Convert complex findings into succinct, actionable insights for both technical and non-technical decision-makers.

• Direct feature definition, model selection, validation, error analysis, sensitivity testing, bias and fairness assessments, and interpretation.

• Set analytical standards and governance for reproducibility, peer review, validation, documentation, version control, and data-quality checks.

• Develop reusable notebooks, SQL scripts, code patterns, templates, Dataverse standards, data dictionaries, and quality checks.

• Mentor analysts, data scientists, and technical teams.

• Coordinate with data engineering, platform, application-development, and Power Platform resources on pipelines, integrations, handoff, monitoring, security, and maintainability.

• Lead technical evaluations of analytical plans, data models, methods, and outcomes.

• Collaborate with data owners and governance stakeholders to enhance definitions, provenance, access, quality, retention, and responsible-use controls.

• Support dashboards, reports, and self-service analytical products.

• Stay updated on data governance, privacy, security, analytical methodologies, Dataverse functionalities, and responsible AI.

⛳️ Requirements

• U.S. citizenship is mandatory.

• Ability to pass a CBP Background Investigation (BI) is required; active CBP BI is preferred.

• A Master's degree or higher in statistics, data science, operations research, public health, computer science, engineering, mathematics, or a related quantitative field.

• Minimum of 9 years of progressive experience in applied data science, advanced analytics, statistical analysis, data engineering, or related analytical roles.

• Experience in federal health, healthcare, regulated-data environments, enterprise modernization, or similarly complex mission-driven organizations.

• Experience leading intricate analytical projects from problem definition through data assessment, analysis, validation, interpretation, and communication.

• Proficient hands-on experience with Python and SQL.

• Experience in designing and evaluating data models, data pipelines, data-quality controls, validation logic, data lineage, authoritative data sources, and reporting-ready datasets.

• Familiarity with advanced analytical techniques including predictive modeling, time-series analysis, causal inference, natural-language processing, machine learning, generative AI, or large language model evaluation.

• Experience with modern data, analytics, and visualization platforms such as Microsoft Dataverse, Databricks, Snowflake, Power BI, Azure, AWS, Google Cloud Platform, or similar technologies.

• Ability to clearly communicate analytical methods, results, uncertainty, assumptions, bias, data-quality issues, and limitations.

• Experience in establishing or applying analytical standards for reproducibility, peer review, documentation, version control, quality assurance, validation, and responsible use of data and AI.

• Technical leadership experience, including mentoring analysts or data scientists, leading peer reviews, developing reusable analytical standards or assets, or managing complex analytical workstreams.

• Willingness to travel 20%, potentially to remote and rugged areas.

• Preferred: doctoral degree; experience in healthcare, federal health, clinical analytics, public health, or operations research; analytics or machine-learning operationalization; NLP, generative AI, or LLM solution evaluation; experience with Dataverse and Microsoft Power Platform; advanced technical certifications; recognized evidence of technical leadership.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Generous retirement plan options.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements and work-life balance initiatives.