Data Scientist I

Data Acquisition, Integration & Management
Acquire, link, and manage large-scale datasets (e.g., Medicaid T-MSIS, commercial claims, EHR/dental EHR)
Develop reproducible pipelines for data ingestion, cleaning, and transformation
Ensure high data quality through validation, auditing, and documentation
Implement scalable workflows for handling longitudinal and multi-source data

Advanced Statistical Analysis & Modeling
Design and implement statistical and quasi-experimental analyses (e.g., regression, survival analysis, causal inference, difference-in-differences)
Apply machine learning methods (e.g., classification, clustering, predictive modeling) where appropriate
Evaluate model performance and ensure interpretability and robustness
Collaborate with investigators to translate research questions into rigorous analytic plans

Programming, Automation & Reproducible Research
Write efficient, well-documented code in R, Python, SAS, or SQL
Build reproducible workflows using version control (e.g., Git) and structured pipelines
Automate repetitive tasks and optimize data processing performance
Maintain clear documentation for all analytic processes to ensure transparency and reproducibility

AI Integration & Responsible Use
Leverage AI tools (e.g., NLP, large language models, automation tools) to enhance productivity and insight generation
Apply AI responsibly with attention to bias, validity, privacy, and reproducibility
Document AI-assisted workflows and ensure all outputs meet scientific rigor standards
Stay current with emerging AI applications in healthcare data science

Data Visualization & Communication
Develop clear, high-quality visualizations and dashboards for diverse audiences
Translate complex analyses into actionable insights for researchers, clinicians, and policymakers
Prepare figures, tables, and analytic summaries for manuscripts, grants, and presentations

Collaboration with Faculty & Research Teams
Work closely with investigators to design studies, define variables, and interpret findings
Provide technical expertise in study design, data structure, and analytic methods
Support interdisciplinary collaboration across clinical, policy, and informatics teams

Data Governance, Security & Compliance
Ensure compliance with HIPAA, DUAs, and institutional data governance policies
Maintain secure data environments and protect sensitive information
Document data provenance, transformations, and analytic decisions

Demonstrated experience working with Medicaid claims, commercial claims, and/or EHR data

Strong programming skills in R and/or Python (SAS/SQL desirable)

Experience with causal inference, longitudinal data analysis, or survival analysis

Familiarity with health services research, policy analysis, or population health

Experience applying machine learning and/or AI methods in healthcare data

Strong track record of clean, well-documented, reproducible code and workflows