Target RWE
Join to apply for the Quantitative Data Scientist role at Target RWE.
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.
Overview In this role, you will be a key contributor within Target RWE’s Quantitative Sciences (QS) organization. You will help ensure that Target’s data are reliable, well‑understood, and ready for scientific and regulatory use. You will work with cross‑functional teams to support high‑quality analyses, contribute to data validation and curation processes, and help build scalable analytic workflows that enable efficient and reproducible real‑world evidence (RWE) generation. Working closely with partners across Product, Engineering, Clinical Operations, Medical Science, and Commercial teams, you will support the design and execution of analyses that demonstrate the value of Target’s data, inform research questions, and contribute to scientific and client‑facing deliverables.
What You’ll Do Data Quality and Stewardship
Help ensure Target’s data are accurate, complete, and ready for analysis.
Contribute to data validation, quality checks, and “fitness-for-use” assessments.
Develop growing expertise in Target’s data structure, provenance, strengths, and limitations.
Support the creation and upkeep of data documentation, dictionaries, and metadata.
Assist in developing scalable processes that promote trust, transparency, and reproducibility.
Analytical Excellence
Support rigorous, reproducible real‑world evidence generation.
Assist in the design and execution of retrospective and prospective analyses using Target RWE datasets.
Write analytic code for descriptive, comparative, and predictive analyses under the guidance of senior scientists.
Contribute to scalable and reusable analytic workflows and code structures.
Apply best practices in coding, version control, methodology selection, and documentation.
Help transform analytic findings into clear visualizations, summaries, and insights.
Support the development of publications, abstracts, and scientific presentations.
Cross‑Functional Collaboration
Work closely with internal teams to translate data into scientific and strategic value.
Collaborate with Product, Engineering, Medical Science, Clinical Operations, and Commercial teams to align on data strategy and analytic priorities.
Participate in internal discussions and occasional client meetings to support data interpretation and analytic understanding.
Share insights about Target’s data assets to help inform decision‑making, product development, and customer‑facing materials.
What You’ll Bring
Master’s degree in biostatistics, epidemiology, health economics, bioinformatics, data science, or a related quantitative field (or equivalent experience).
3–5 years of experience working with real‑world data (e.g., EMR, claims, registry, or clinical trial data).
Strong programming skills in R and familiarity with reproducible analytic workflows.
Experience with data cleaning, validation, quality checks, or curation processes.
Demonstrated ability to write clear, maintainable, well‑documented code.
Strong analytical, problem‑solving, and conceptual thinking skills.
Excellent communication and collaboration skills with technical and scientific partners.
Ability to translate analytic outputs into clear, actionable insights.
What We Offer You
Hybrid + remote work environment
Comprehensive health, dental, and vision for you and your family
401(k) with company match
Generous PTO and company holidaysPaid parental leave
Hybrid role: Located in Research Triangle Park, North Carolina
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
#J-18808-Ljbffr
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.
Overview In this role, you will be a key contributor within Target RWE’s Quantitative Sciences (QS) organization. You will help ensure that Target’s data are reliable, well‑understood, and ready for scientific and regulatory use. You will work with cross‑functional teams to support high‑quality analyses, contribute to data validation and curation processes, and help build scalable analytic workflows that enable efficient and reproducible real‑world evidence (RWE) generation. Working closely with partners across Product, Engineering, Clinical Operations, Medical Science, and Commercial teams, you will support the design and execution of analyses that demonstrate the value of Target’s data, inform research questions, and contribute to scientific and client‑facing deliverables.
What You’ll Do Data Quality and Stewardship
Help ensure Target’s data are accurate, complete, and ready for analysis.
Contribute to data validation, quality checks, and “fitness-for-use” assessments.
Develop growing expertise in Target’s data structure, provenance, strengths, and limitations.
Support the creation and upkeep of data documentation, dictionaries, and metadata.
Assist in developing scalable processes that promote trust, transparency, and reproducibility.
Analytical Excellence
Support rigorous, reproducible real‑world evidence generation.
Assist in the design and execution of retrospective and prospective analyses using Target RWE datasets.
Write analytic code for descriptive, comparative, and predictive analyses under the guidance of senior scientists.
Contribute to scalable and reusable analytic workflows and code structures.
Apply best practices in coding, version control, methodology selection, and documentation.
Help transform analytic findings into clear visualizations, summaries, and insights.
Support the development of publications, abstracts, and scientific presentations.
Cross‑Functional Collaboration
Work closely with internal teams to translate data into scientific and strategic value.
Collaborate with Product, Engineering, Medical Science, Clinical Operations, and Commercial teams to align on data strategy and analytic priorities.
Participate in internal discussions and occasional client meetings to support data interpretation and analytic understanding.
Share insights about Target’s data assets to help inform decision‑making, product development, and customer‑facing materials.
What You’ll Bring
Master’s degree in biostatistics, epidemiology, health economics, bioinformatics, data science, or a related quantitative field (or equivalent experience).
3–5 years of experience working with real‑world data (e.g., EMR, claims, registry, or clinical trial data).
Strong programming skills in R and familiarity with reproducible analytic workflows.
Experience with data cleaning, validation, quality checks, or curation processes.
Demonstrated ability to write clear, maintainable, well‑documented code.
Strong analytical, problem‑solving, and conceptual thinking skills.
Excellent communication and collaboration skills with technical and scientific partners.
Ability to translate analytic outputs into clear, actionable insights.
What We Offer You
Hybrid + remote work environment
Comprehensive health, dental, and vision for you and your family
401(k) with company match
Generous PTO and company holidaysPaid parental leave
Hybrid role: Located in Research Triangle Park, North Carolina
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
#J-18808-Ljbffr