Data Scientist

About the Role

Headwater Science is a data science and methods company specializing in principled, reproducible evidence generation for complex clinical and regulatory challenges.

In this role, you will support research projects by transforming source data from healthcare databases into analytic-ready data sets, performing statistical analyses, and generating reports of the results. You will work with small teams of epidemiologists and statisticians, focusing primarily on executing specifications outlined in study protocols/statistical analysis plans (SAP) and building reproducible analytical pipelines that are understandable, well documented, and compliant with quality control standards.

Key Responsibilities

• Writing R code to execute research projects:
• Building cohorts.
• Running analyses that produce results.
• Transforming raw healthcare databases into analytic-ready data sets:
• Working with deidentified administrative claims and electronic health record (EHR) data.
• Drawing on domain knowledge of database conventions to make appropriate choices when building study variables.
• Using dbplyr to query source databases from R, generating SQL.
• Applying eligibility criteria from a study protocol and/or SAP to identify the study population.
• Determining the index date and start of follow-up for each patient.
• Building the analytic data set (often one row per patient).
• Supporting analysis and reporting:
• Fitting models specified in the study design, often using causalRisk.
• Running diagnostics on the analysis (e.g., checking propensity score distributions, weight behavior, covariate balance).
• Producing tables and figures for study results (e.g., baseline characteristics, effect estimates, risk curves, treatment patterns).
• Assembling results into client deliverables.
• Building project repositories as orchestrated pipelines that reliably reproduce study results.
• Participating in quality control procedures:
• Code review.
• Testing.
• Double coding of portions of an analysis.
• Collaborating closely with the study design team throughout the study lifecycle.

Requirements & Tech Stack

• Strong programming skills in R.
• Experience querying relational databases using SQL or interfaces like dbplyr.
• Experience writing reproducible code.
• Strong communication, presentation, and collaboration skills.
• Tools used include: GitLab.

Qualifications

• Master's degree, or two or more years of relevant work experience, in biostatistics, epidemiology, health economics, bioinformatics, data science, or a related quantitative field.
• Experience with real-world healthcare data (e.g., administrative claims, EHR, hospital chargemaster, registry data).
• Experience constructing longitudinal data sets for observational research.