Senior Data Scientist

The Senior Data Scientist at Institute For Medical Research Inc will help advance clinical research and quality-improvement work for the Durham VA Cardiology program. The position combines clinical informatics, biostatistics, data engineering, and workflow automation to move from study planning and data sourcing through analysis, reporting, and dissemination.

Working onsite in Durham, NC, you will partner with cardiology stakeholders and research teams to translate clinical and research questions into reliable datasets, rigorous statistical analyses, and practical reporting tools that can be sustained across current and future studies.

• Collaborate with clinical investigators to define cohorts, outcomes, exposures, time windows, and data requirements for observational studies, clinical trials, implementation projects, and quality-improvement initiatives.
• Extract, integrate, transform, and curate structured clinical data from the VA Corporate Data Warehouse and other approved sources, including laboratory, medication, procedure, diagnosis, encounter, vital-sign, and longitudinal follow-up data.
• Build reusable, well-documented data pipelines, analytic datasets, data dictionaries, validation checks, and source-to-output traceability procedures.
• Conduct systematic data quality assessment, covering completeness, consistency, duplicate identification, temporal validation, and reconciliation with clinical or operational source systems.
• Provide statistical programming and analytic support using methods appropriate to the study design, including descriptive, inferential, regression, longitudinal, survival, and other analyses.
• Support study design and feasibility by contributing to analytic plans, variable definitions, sample-size considerations, interpretation of findings, and sensitivity or subgroup analyses.
• Create validated tables, listings, figures, visualizations, and summary reports for investigators, sponsors, clinical teams, and leadership.
• Help prepare protocols, abstracts, manuscripts, presentations, grant applications, and other scientific deliverables, including analytic documentation and methods sections.
• Design and maintain research data-capture, workflow, and reporting solutions using platforms such as REDCap
  , Power BI
  , Share Point ,
  Power Automate
  , and other approved tools.
• Automate processes such as patient identification, eligibility screening, task generation, follow-up scheduling, reminders, notifications, missing-data review, and escalation of overdue activities.
• Develop operational and research dashboards to track enrollment, follow-up, data completeness, clinical measures, study milestones, and agreed performance indicators.
• Partner with end users to test, document, refine, and sustain reporting tools and automated workflows while reducing unnecessary manual processing.
• Evaluate and apply advanced statistical, predictive, or machine-learning methods when appropriate, aligned to the clinical question, data available, study maturity, and validation needs.
• Support Cardiology research involving ECG and echo cardiographic data, including development and evaluation of prediction models with emphasis on clinical interpretability, reproducibility, and generalizability.
• Develop and implement reproducible machine-learning pipelines, covering data preparation, quality control, model development and evaluation, validation, and reporting.
• Assess new analytic methods and data sources and recommend practical approaches that complement established clinical informatics and biostatistical workflows.
• Serve as a data-science and informatics resource for Cardiology investigators and multidisciplinary teams, communicating technical findings clearly to both technical and nontechnical audiences.
• Apply applicable VA privacy, information-security, regulatory, and research-governance requirements across data access, processing, analysis, reporting, and dissemination.
• Promote reproducible research through version control, standardized programming practices, transparent documentation, validation, and clear communication of analytic assumptions and limitations.
• Provide technical guidance or mentorship to analysts, trainees, investigators, and project staff as needed.

• Advanced training or equivalent professional experience in data science, biostatistics, biomedical or clinical informatics, epidemiology, engineering, computational biology, or a related quantitative field.
• Substantial experience analyzing complex clinical,…