Lead a multidisciplinary team to generate high-quality clinical intelligence and evidence across the Breast & Gynaecology portfolio using real-world evidence and AI.
Compensation
The annual base pay for this position ranges from $ 203.213,60 - 304.820,40 Annual USD. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program.
Responsibilities
Define and evolve the Clinical Intelligence & Evidence strategy for Breast & Gynaecology
Provide scientific leadership in epidemiology and Real-World Evidence
Work closely with drug development teams to translate clinical and portfolio questions into research objectives
Apply Real-World Evidence to support clinical development questions
Shape the appropriate use of machine learning and AI within Real-World Evidence
Requirements
Advanced degree (PhD, MPH, MD, or MSc) in Statistics, Epidemiology, Public Health, Data Science, Mathematics, or related field
Nice to have: Oncology breast and/or gynaecological cancers
The annual base pay for this position ranges from $ 203.213,60 - 304.820,40 Annual USD. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program.
Responsibilities
Define and evolve the Clinical Intelligence & Evidence strategy for Breast & Gynaecology
Provide scientific leadership in epidemiology and Real-World Evidence
Work closely with drug development teams to translate clinical questions into research objectives
Apply Real-World Evidence to support clinical development questions
Shape the appropriate use of machine learning and AI within Real-World Evidence
Requirements
Advanced degree (PhD, MPH, MD, or MSc) in Statistics, Epidemiology, Public Health, Data Science, Mathematics, or related field
Nice to have: Experience within Oncology, particularly Breast and/or Gynaecological cancers
Nice to have: Hands-on experience in data science, machine learning and predictive modelling
Nice to have: Familiarity with advanced approaches such as Bayesian inference, temporal modelling, multimodal modelling, foundation models, and model interpretability and evaluation
Nice to have: Experience with clinical text, electronic health records, imaging or molecular data, including genomics in clinical care or translational medicine
M
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Magnum RFM Ice Cream, Inc. (Selecta Philippines) · Posted Nov 5, 2026
