Senior Data Analyst

Labcorp•Durham, NC

11d•$80,000 - $120,000•Hybrid

About The Position

Labcorp has an exciting new "big data" approach to diagnostic testing. We are integrating test results from our national testing business into an enterprise data warehouse to enable a variety of impactful data use cases. We have an excellent opportunity for a highly motivated analyst within our Real World Data (RWD) group. As a Real-World Data, Senior Data Analyst, you will work alongside software engineers, clinicians, data scientists, and informaticists to turn complex testing data into clear, actionable analyses. You'll spend most of your time in SQL and Python — pulling cohorts, investigating data quality issues, and producing the reports and dashboards that internal and external stakeholders rely on. This role is a great fit for someone who enjoys digging into messy healthcare data, asking sharp questions of it, and communicating what they find.

Requirements

Bachelor's degree in a STEM, quantitative, or health-related field
3 years or more of analytics experience
3 years of demonstrated experience analyzing healthcare, diagnostic, or life-sciences data in a professional setting.
5 years or more of experience using SQL, including writing and optimizing complex queries against large relational databases.
3 years or more of using Python for data analysis (pandas, numpy, and common plotting libraries).
2 years or more of experince with Git and version-controlled workflows (pull requests, code review, branching).
2 years or more of experience building dashboards in Tableau, Power BI, or similar tools.
Comfort working in modern data environments such as Databricks, Snowflake, or Jupyter notebooks.
Awareness of HIPAA and the handling requirements for PHI in analytic environments.
Experince translating vague business questions into concrete, answerable analyses.
Comfortable in presenting findings to both technical and non-technical audiences, including clinicians and commercial stakeholders.
Strong sense of ownership and follow-through on analyses from question to delivered answer.

Nice To Haves

Master’s degree in STEM, quantitative, or health-related field
2 or more years of hands-on experience working with diagnostic, clinical, or other healthcare data is required. Examples include molecular diagnostics results (NGS, histopathology), EMR/EHR data, claims data, LIMS data, or laboratory test results.
2 years or more of working with healthcare data.
2 years or more years of experience with healthcare data standards and ontologies (SNOMED, LOINC, ICD-10, CPT) is a plus.
3 years or more of experience using cloud data platforms (AWS, Azure, or GCP) is a plus.
2 years or more of experience working on Agile teams (sprints, stand-ups, ticket-based workflows).
Familiarity with FAIR data principles.
Exposure to Real-World Evidence (RWE), HEOR, or Medical Affairs workflows.

Responsibilities

Write SQL and Python to extract, transform, and analyze patient-level oncology data from our enterprise data warehouse.
Identify and define patient cohorts of interest in support of internal research and commercial activities, clearly documenting inclusion/exclusion logic and caveats.
Build and maintain dashboards and recurring reports that make RWD accessible to non-technical stakeholders.
Investigate data quality issues — tracing anomalies back through pipelines, comparing against source systems, and working with engineers to resolve root causes.
Produce data quality metrics and monitoring to confirm pipelines are operating as expected.
Partner with data scientists and clinicians to prepare analytic datasets, validate outputs, and interpret results in a clinical context.
Document analyses, queries, and methodologies in version-controlled repositories so that work is reproducible and reviewable.
Contribute to ad hoc analyses supporting RWD publications, conference presentations, and client-facing deliverables.