Principal, Quantitative Scientist
About the role
We are seeking a Principal to join Target RWE’s Quantitative Sciences (QS) organization. This is a highly cross-functional and client-facing role.
Responsibilities
Ensure that Target’s analyses are scientifically rigorous, practical, and aligned with real-world use.
Guide the design of observational studies using real-world data, including retrospective and prospective analyses.
Apply statistical and epidemiologic methods in a practical, fit-for-purpose way.
Develop and review study protocols and statistical analysis plans.
Ensure analyses are reproducible, interpretable, and aligned with regulatory and scientific expectations.
Partner with internal teams to translate research questions into practical analytic approaches.
Serve as a key scientific voice in client and partner interactions.
Participate in and lead client meetings to explain study design, methodology, and results.
Translate complex analytical concepts into clear, accessible language for diverse audiences.
Support business development efforts by helping communicate Target’s scientific approach and data value.
Represent Target in external settings, including conferences, scientific collaborations, and partner discussions.
Build trust with clients by providing thoughtful, pragmatic, and credible scientific guidance.
Connect data, analytics, and business needs across the organization.
Partner closely with Product, Engineering, Medical Science, Clinical Operations, and Commercial teams.
Help shape analytic strategies that align with both scientific goals and customer needs.
Provide guidance to the Quantitative Sciences team on study design and interpretation.
Mentor team members on balancing methodological rigor with practical execution.
Contribute to internal best practices for scalable, high-quality evidence generation.
Requirements
PhD or MS in biostatistics, epidemiology, health economics, data science, or a related field.
10+ years of experience working with real-world data (EMR, claims, registry, or clinical trial data).
Strong foundation in observational study design and applied statistical methods; experience with real-world pragmatic clinical trial designs is a plus.
Demonstrated ability to apply methods pragmatically, selecting the right approach for the problem.
Willingness to engage directly with data and analyses as needed, with working knowledge of R and/or SQL to support exploratory work, validation, and collaboration with analytic teams.
Experience working directly with clients or external partners in life sciences or healthcare.
Excellent communication and presentation skills, with the ability to explain complex concepts clearly.
Comfortable operating in client-facing settings, including meetings, presentations, and scientific discussions.
Strong collaboration skills across technical and non-technical teams.