United States flag

Senior Manager, Medical Affairs - Real World Evidence Epidemiologist

United States - California - Santa Monica, United States – RemoteMedical AffairsRegular

Job Description

Epidemiologist will report to Kite Medical Affairs RWD Platform Lead to conduct timely, relevant, and rigorously analysis of RWD to address critical research questions as well as contribute to (cross-) functional initiatives. The epidemiologist will have access to real-world databases in-licensed across Gilead and Kite and act as the stewards of Gilead's and Kite’s best practices, standards, and methodologies underlying the use of real-world data (RWD).

The epidemiologist will be responsible for leading and supporting epidemiologic studies using RWD to support product strategy and conduct disease epidemiology, natural history, treatment patterns, and outcomes studies. The epidemiologist will work closely with key internal and external stakeholders to design the study (develop protocol and statistical analysis plan), to execute the planned analysis in collaboration with members of the biostatistics and programming team, and to communicate the results internally and externally.  The epidemiologist will work closely with project team to manage timeline and workflow.

The epidemiologist will contribute to cross- functional initiatives and collaborate with Kite Biometrics team and the RWE analytics group within the Clinical Data Sciences – RWE organization of Gilead. The epidemiologist will be steward for best pharmacoepidemiology and pharmacovigilance practices.

Key Responsibilities

  • Lead or support development of study protocol, reports, and manuscripts for research projects using RWD (e.g., claims and EHR) and publicly available database, e.g., NPI database
  • Lead or support development of statistical analysis plan for descriptive and complex studies using RWD, including claims (open and closed), and EHR in collaboration with internal researchers
  • Lead or support generation of code lists and identification of claims- or other RWD-based algorithms applicable to RWD research, by working collaboratively with internal/external researchers and/or via literature review
  • Collaborate closely with the internal stakeholders, e.g., biostatistics and programming team members to execute planned data analyses
  • Support cross-functional initiatives to develop and refine internal procedures, workflows, and best practices
  • Manage project timeline and deliverable for studies executed internally, e.g., ensuring there is close alignment, escalating concerns promptly

Basic Qualifications

Doctorate

OR

Master’s and 6+ years of epidemiology or real-world data experience

OR

Bachelor’s and 8+ years of epidemiology or real-world data experience

OR

Associate and 10+ years of epidemiology or real-world data experience

OR

High School Diploma/GED and 12+ years of epidemiology or real-world data experience

Preferred Qualifications

  • Doctorate Degree in Statistics, Biostatistics, Epidemiology or related discipline from an accredited institution and 2 years of experience working with a broad range of RWD, in academia, at a contract research organization, or in the biopharmaceutical industry
  • Knowledge of real-world data (RWD) and application of RWD to observational research; in-depth knowledge of administrative claims, curated and un-curated electronic health records
  • Demonstrated proficiency in statistical analysis programs commonly used in life sciences (e.g., SAS, R). Proficiency in additional programming languages
  • Experience using RWD for regulatory studies (e.g., PMR, PASS) studies, experience working with Sentinel Initiative Query, experience in pharmacovigilance
  • Experience in data mining (predictive model, large data mining)
  • Understanding of the principles of epidemiologic research methods
  • Experience with advanced methods and programming to support complex study designs, e.g., high-dimensional propensity score/disease risk score
  • Experience in biopharmaceutical industry
  • Ability to effectively communicate statistical methodology and analysis results
  • Ability to work effectively in a constantly changing, diverse, and matrix environment
  • Oncology research experience

#LI-ML1