Healthcare Data Scientist — Causal Analytics & Pipelines

Headwater Science; North Carolina; Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work environment

Health, dental, and vision coverage

401(k) with company match

Generous PTO and company holidays

Paid parental leave

Job summary

Headwater Science, a data science and methods company, seeks a researcher to transform healthcare data into analytic-ready datasets, perform analyses, and generate reports. You will collaborate with a small team of epidemiologists and statisticians on study protocols and reproducible pipelines.

You will primarily write R code to build cohorts, execute analyses, and produce client-ready deliverables, following SAP-guided specifications and QC standards.

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.
• Strong programming skills in R.
• Experience querying relational databases, whether directly in SQL or through an interface like dbplyr.
• Experience writing code that others can read, run, and reproduce.
• Strong communication, presentation, and collaboration skills with cross-functional technical and scientific teams.
• Nice to Have: Experience with real-world healthcare data, such as administrative claims, EHR, hospital chargemaster, or registry data.
• Experience constructing longitudinal data sets for observational research.

Responsibilities

• Draw on domain knowledge of how each database represents clinical events to make appropriate choices when building study variables.
• Use dbplyr to query source databases from R, generating SQL against tables that are often too large to hold in memory.
• Apply eligibility criteria from a study protocol and/or SAP to identify the study population.
• Determine the index date and start of follow-up for each patient.
• Build the analytic data set — often one row per patient, with columns for baseline characteristics, changes in treatment and health status over time, outcomes of interest, and censoring.
• Fit the models specified in the study design, often using causalRisk , our internal package for causal inference with observational data.
• Run diagnostics on the analysis — such as checking propensity score distributions, weight behavior, and covariate balance — and flag problems back to the study design team.
• Produce the tables and figures that make up the study results — baseline characteristics, effect estimates, and study-specific outputs like risk curves and treatment patterns — and assemble them into client deliverables.
• Build project repositories as orchestrated pipelines that reliably reproduce the study results each time they are run.
• Participate in quality control procedures including code review, testing, and double coding of portions of an analysis as an independent check on the primary implementation.
• Work closely with the study design team throughout the study lifecycle, incorporating changing requirements, sharing interim results, and providing feedback on how well the study design suits the available data.

Skills

R

SQL

dbplyr

Code readability

Communication & collaboration

Education

Master's degree or 2+ years of relevant work experience

Tools

dbplyr

Job description

Headwater Science, a data science and methods company, seeks a researcher to transform healthcare data into analytic-ready datasets, perform analyses, and generate reports. You will collaborate with a small team of epidemiologists and statisticians on study protocols and reproducible pipelines.

You will primarily write R code to build cohorts, execute analyses, and produce client-ready deliverables, following SAP-guided specifications and QC standards.