Senior Quantitative Data Scientist

Target RWE•Raleigh, NC

40d•$120,000 - $150,000•Hybrid

About The Position

At Target RWE, our mission is driven by a deep commitment to people, whether it’s the patients we serve, the partners we collaborate with, or the dedicated team members who power our work. As a purpose-driven organization, we leverage real-world data to advance clinical research and inform better healthcare decisions. We foster a collaborative environment where every voice is heard, every idea has an impact, and every contribution helps improve lives. If you're seeking a place where your work truly matters, join us to advance science. In this role, you will be a foundational member of Target RWE’s Quantitative Sciences (QS) organization, helping to establish Target as a leader in rigorous, reproducible, and regulatory-grade evidence generation. You will serve as a scientific owner of Target’s data, developing deep expertise in its structure, quality, and applications while helping to build scalable data validation, curation, and analytic processes that ensure reliability and usability. Working closely with cross-functional partners in Product, Engineering, Clinical Operations, and Medical Science, you will design and execute analyses that demonstrate the value of Target’s data, support customers across life sciences, regulatory, and academic settings, and build scalable, standardized analytic approaches for real-world evidence generation.

Requirements

Advanced degree (MS or PhD) in biostatistics, epidemiology, health economics, bioinformatics, data science, or a related quantitative field.
5+ years of experience working with real-world data (e.g., EMR, claims, registry, or clinical trial data).
Strong programming expertise in R, and experience with reproducible analytic frameworks.
Proven expertise in data quality assessment, validation, and curation workflows.
Demonstrated ability to build and maintain reproducible coding practices and scalable analytic processes that enable efficiency, transparency, and consistency across studies.
Strong communication, presentation and collaboration skills with cross-functional technical and scientific teams.
Demonstrated ability to translate data insights into actionable scientific or business recommendations.

Responsibilities

Data Ownership and Quality
Ensure Target’s data are accurate, complete, and fit for regulatory and scientific use by building systems and practices that establish trust in data integrity and readiness for analysis.
Develop deep expertise in Target’s data, understanding its structure, provenance, strengths, and limitations.
Design and implement validation frameworks, data quality checks, and “fitness-for-use” assessments.
Create and maintain data dictionaries and documentation that promote transparency and reproducibility.
Analytical excellence
Support the design and execution of retrospective and prospective studies using Target’s data assets.
Develop statistical analysis plans and analytic code for descriptive, comparative, and predictive analyses.
Design and implement scalable, reusable analytic frameworks and modular code structures that support consistent execution across therapeutic areas and data products.
Apply best practices in methodology, version control, code review, and documentation to ensure reproducibility.
Translate complex results into clear visualizations and insights for scientific, regulatory, and client audiences.
Contribute to publications, abstracts, and collaborations that advance Target’s scientific reputation and influence.
Cross functional partnership
Partner closely with Commercial, Medical Science, Product, Data Insights, Engineering, and Clinical Operations teams to align on data strategy and analytic priorities.
Serve as the internal “voice of the customer,” anticipating how clients, regulators, and researchers will use Target’s data.
Participate in client and partner meetings to demonstrate the validity and value of Target’s data products.
Leverage your deep knowledge of Target’s data assets to guide internal teams and external partners, anticipating analytical and operational challenges and helping to shape data use strategies.
Translate analytic findings and data characteristics into clear, client-facing materials that demonstrate Target’s data quality, representativeness, and scientific utility.