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Senior Scientist-Health Economic Resources

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Scientist-Health Economic Resources in Plainsboro, NJ (Hybrid) for 6+ months, paying an undisclosed rate. Requires a graduate degree, 3+ years in RWE and epidemiology, and proficiency in SAS, R, and Python. Oncology experience preferred.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
488
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πŸ—“οΈ - Date
December 25, 2025
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Plainsboro, NJ
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Quality Assurance #Regression #SAS #Datasets #Programming #Python #R #ML (Machine Learning) #Statistics #Databases #Compliance
Role description
Only local candidate needed. NO C2C Please do not apply if you are staying outside of New Jersey. Job Title: Senior Scientist-Health Economic Resources Location: Plainsboro, NJ 08536 (Hybrid) Duration: 6+ Months Position Overview We are seeking a Senior Scientist, Health Economic Resources / Real-World Evidence (RWE) to support the design, execution, and communication of observational studies using diverse real-world data (RWD) sources. This role focuses on generating evidence to demonstrate unmet medical need, product value, and differentiation for clinical development, market access, regulatory, and health-policy decision-making. This position supports the Center for Outcomes Research, Real World Evidence and Epidemiology (CORE) and reports to the Head of RWD & Epidemiology Analytics. The role requires strong technical expertise in epidemiology, advanced analytics, and AI-driven methodologies. Key Responsibilities β€’ Support implementation of strategies to demonstrate unmet disease needs with outcomes meaningful to payers, clinical decision-makers, and regulators. β€’ Assist with research to generate evidence supporting: β€’ Product differentiation and value for commercial and market access needs β€’ Clinical development, regulatory, and safety requirements through RWE and epidemiology studies β€’ Partner with CORE asset leads to design and execute RWE studies through hands-on analytics. β€’ Evaluate and assess emerging data modalities (e.g., claims, EHR, registries, social determinants of health, genomics, biomarkers, clinical notes) to ensure optimal data-source selection. β€’ Execute studies including development of table shells, analytic datasets, analysis plans, programming, statistical methods, and quality control in compliance with regulatory and scientific standards. β€’ Manage projects and external vendors/partners supporting CORE initiatives. β€’ Conduct quality assurance, code validation, and programming review. β€’ Explore, pilot, and scale AI-driven analytics applications within RWD and epidemiology workflows. β€’ Draft analysis reports and support publications and presentations at scientific conferences and forums. β€’ Collaborate cross-functionally with development, commercial, market access, safety, legal, and medical affairs teams. β€’ Support communication and publication strategies for assigned products. Required: β€’ Graduate degree (PhD or Master’s) in Epidemiology, Biostatistics, Public Health, or a related field. β€’ 3+ years of experience in real-world evidence generation and epidemiology analytics. β€’ Working knowledge of healthcare data sources, including: β€’ Claims databases β€’ Electronic health records (EHR) β€’ Hospital billing data β€’ Cancer registries (e.g., SEER) β€’ Linked and longitudinal datasets β€’ Strong understanding of epidemiologic and statistical concepts (e.g., confounding, bias, incidence, regression models, survival analysis). β€’ Experience applying statistical methods used in outcomes research and epidemiology, such as: β€’ Survival analysis and modeling β€’ Regression analysis β€’ IPTW, MAIC, and causal inference techniques β€’ Hands-on proficiency in statistical programming (SAS, R, Python) using real-world oncology claims/EHR data. β€’ Experience with AI/ML frameworks applied to healthcare data. Preferred: β€’ Oncology experience