Must have hands‑on experience working with real‑world healthcare data (claims, Optum, MarketScan, Medicare, etc.) Strong Statistical Background Regression, survival analysis, longitudinal modeling, observational study design Experience in pharma, biotech, healthcare analytics, or consulting supporting those environments Python or R + Large Data Handling Ability to work with large datasets (Spark, SQL, cloud environments preferred) End‑to‑End Ownership Must be able to take ambiguous problems and independently deliver structured, defensible analysis Nice to Have HEOR / Medical Affairs / Market Access exposure Causal inference experience Oncology or complex disease experience Publication or research background Focus on candidates who: Have strong communication skills Have true healthcare/RWE exposure (not generic DS) Senior Data Scientist – Real World Evidence (RWD/RWE) Analytics Role Summary We are seeking a Senior Data Scientist specializing in Real‑World Data (RWD) and Real‑World Evidence (RWE) analytics to join our Advanced Analytics organization. This role will support Client’s portfolio by leading analytics using large‑scale healthcare data sources—including Optum Claims and other real‑world datasets —to generate evidence that informs asset strategy, medical affairs, HEOR, and commercialization decisions. The successful candidate will independently lead end‑to‑end analytical work: translating business and scientific questions into analytic strategies, shaping complex claims and longitudinal healthcare data into analysis‑ready assets, applying rigorous statistical and machine learning approaches, and communicating insights clearly to cross‑functional stakeholders. This role requires strong judgment, comfort with ambiguity, and deep experience working with observational healthcare data. Key Responsibilities Own and deliver analyses using administrative claims and linked real‑world datasets to address questions related to disease burden, treatment patterns, outcomes, healthcare utilization, and comparative effectiveness. Partner closely with Medical Affairs, HEOR, Clinical Development, Market Access, and Commercial teams to understand questions, refine analytic intent, and deliver decision‑ready evidence aligned with product and program needs. Design observational studies Develop and execute fit‑for‑purpose observational study designs (e.g., cohort construction, longitudinal follow‑up, baseline characterization, outcome definition), ensuring methodological rigor and transparency. Apply statistical and ML methods to RWD Select, implement, and validate appropriate statistical and machine learning approaches (e.g., regression, survival analysis, longitudinal modeling, predictive models) while addressing real‑world data challenges such as confounding, bias, missingness, and coding variability. Engineer and manage large‑scale claims data Perform data wrangling, feature engineering, and reproducible data pipelines using large Optum claims datasets and related sources in modern compute environments (e.g., Spark, cloud‑based platforms, Microsoft Fabric or equivalent). Ensure analytic quality and defensibility Produce well‑documented, reproducible analyses suitable for internal decision‑making, congress abstracts, manuscripts, and cross‑functional review; clearly articulate assumptions, limitations, and sources of uncertainty. Translate complex analytic results into clear narratives, visuals, and recommendations tailored to technical and non‑technical audiences. Be a team multiplier Collaborate effectively within Advanced Analytics, mentor junior team members where appropriate, and contribute to best practices for RWD/RWE analytics. What Success Looks Like You bring structure to ambiguous RWE questions and independently drive analyses from concept to delivery. Stakeholders trust your work because it is rigorous, transparent, and clearly communicated. You balance methodological rigor with practical decision needs in a fast‑moving portfolio environment. Your analyses are reusable, reproducible, and scalable across assets and indications. Core Qualifications 4+ years of experience in data science, biostatistics, or analytics with a strong focus on real‑world data / real‑world evidence in pharma, biotech, consulting, or a related healthcare setting. Hands‑on experience working with large administrative claims datasets , preferably Optum Claims or similar (e.g., MarketScan, Medicare, Medicaid), including patient‑level longitudinal analyses. Strong foundation in statistical reasoning and applied methods for observational data (e.g., regression modeling, survival analysis, longitudinal analyses, covariate adjustment). Proficiency in Python and/or R , with experience handling large‑scale datasets in distributed or cloud‑enabled environments (e.g., Spark, SQL‑based analytics). Demonstrated ability to create analysis‑ready cohorts, features, and outcomes from raw claims data. Strong communication skills with the ability to explain methods, assumptions, and findings to cross‑functional, non‑technical audiences. Highly collaborative, with the ability to build credibility and productive partnerships across functions. Nice to Have Experience generating RWE to support medical affairs, HEOR, market access, or regulatory interactions . Familiarity with causal inference concepts and methods applied to observational data. Experience supporting assets in oncology, dermatology, hematology , or other complex therapeutic areas. Prior authorship or contribution to conference abstracts or peer‑reviewed RWE publications . #J-18808-Ljbffr