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Director, Data & Epidemiology; RWD & EPI Analytics

Job in Freehold, Monmouth County, New Jersey, 07728, USA
Listing for: The Antibody Society
Full Time position
Listed on 2026-02-12
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Scientist, Data Security
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Director, Real World Data & Epidemiology (RWD & EPI) Analytics

Overview

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking medicines that change lives and the future of cancer treatment and serious diseases. We strive to create a global workplace where individuals' unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees. Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science.

We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose.

Does this inspire you and feel like a fit? Then we would love to have you join us!

Role

The Director of Real-World Data & Epidemiology (RWD & Epi) Analytics will lead the design, execution, and communication of observational studies using diverse RWD sources. This role combines strategic leadership, deep technical expertise in observational study design and execution, data and analytic infrastructure development, and advanced AI-driven analytics to deliver evidence that informs clinical development, market access, and health-policy decisions. This position reports to the Head of RWD & Epi analytics at Center for Outcomes Research, Real World Evidence and Epidemiology (CORE).

Responsibilities
  • Collaborate with CORE asset leaders to design, execute, and report on observational and epidemiologic studies in support of assigned assets and indications—from feasibility analyses and protocol development, RWE/Epi methods advice, to data analysis and final reporting.
  • Conduct feasibility assessments to match study objectives with optimal RWD sources (claims, EHR, registries, patient-generated data).
  • Collaborate with CORE asset leaders to conduct survival and economic modeling to support HTA activities.
  • Execute studies by managing table shells, analytic data file, analysis plan, programming, statistical methods, and quality control per regulatory and scientific standards.
  • Present study designs, interim analyses, and final results to study team, translating complex findings into actionable insights for both technical and non-technical audiences.
  • Evaluate new and emerging data modalities (e.g., claims, EHR, social determinants of health, genomics, biomarkers, clinical notes) for study applicability and integrate them into the evidence-generation framework.
  • Lead pilots and scale successful AI applications in routine RWD & Epi analytics.
  • Partner with CORE asset leaders to define evidence needs, set realistic timelines, and manage expectations.
  • Mentor and coach RWD & Epi scientists and programmers, fostering technical growth in study methods, programming skills, and critical thinking.
  • Define and implement standardized processes and governance for study execution, data management, and documentation within the analytic environment.
  • Evolve and scale the data and analytics infrastructure—partnering with DD&AI to streamline pipelines, ensure reproducibility, and maintain data security and compliance.
  • As a member of the CORE team, contribute to department strategy and objectives as well as represent CORE on key initiatives.
Requirements
  • Graduate (PhD or Masters) degree in Epidemiology, Biostatistics, Public Health, or related field.
  • 10+ years' experience in real-world evidence generation and epidemiology analytics.
  • Demonstrated expertise in observational study design, statistical methods (survival analysis/modeling, regression analysis, IPTW, MAIC, causal inference, etc), and RWD evaluation.
  • Hands-on proficiency in statistical programming (SAS, R, Python) on real-world claims/EHR data and AI/ML frameworks.
  • Exceptional communication, presentation, and stakeholder-management skills.
  • Oncology experience preferred
  • Strong commercial and clinical strategic mindset.
  • Demonstrated research accomplishments as evidenced by a history of peer-reviewed publications.
  • Ability to work well in a team and cross-functional environment, as well as independently with limited supervision.
  • Ability to work successfully under pressure in a fast-paced environment and with tight timelines.
  • Ability to be proactive, enthusiastic and goal…
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