Associate Director – Computational Biology, Cardiovascular, Metabolic, Obesity and Related

Responsibilities

• The Computational Biology group in the Center for Technology and Innovation (CfTI) within the Precision Medicine organization is seeking a highly motivated Computational Biologist with expertise in analyzing clinical biomarker data
• This role will contribute to advancing clinical programs and studies by integrating computational biology and bioinformatics techniques with biological and clinical data
• Support CVMet and OaR teams as a Comp Bio Therapeutic Area Lead and Global Biomarker Analysis Lead
• Develop biomarker analysis plans to support precision medicine, evidence generation and reverse translation during clinical development of therapeutic molecules
• Define and execute workflows for biomarker data analysis, integrating multiple omics, imaging and digital biomarkers, integrated with clinical metadata and outcomes
• Lead the analysis and interpretation of clinical biomarker data from various assay platforms
• Support the generation of evidence for target engagement evaluation, patient stratification, response prediction, indication selection, assay development, and diagnostic development
• Collaborate cross-functionally with early development teams, biostatistics, clinical pharmacology, precision medicine leads, clinical biomarker leads, and research teams to manage data integration, analysis, and presentation
• Support internal and external presentations with fit-for-purpose analysis insights and messaging and support the development of publications

• Doctorate degree [and relevant post-doc where applicable] and 4 years of scientific experience OR Master’s degree and 7 years of scientific experience OR Bachelor’s degree and 9 years of scientific experience
• PhD in Bioinformatics, Mathematics, Computer Science, Computational Biology or Data Science, with a minor or robust background in Biology
• A background in cardiovascular diseases, obesity and chronic weight management, and other metabolic diseases is highly preferred
• Hands‑on experience in statistical modeling, machine learning, and AI applied to clinical biomarker and clinical efficacy data
• A strong understanding and practical skills in statistics and their use in data analysis for clinical settings
• Proven expertise in analyzing multi‑modal, multi‑dimensional, and large‑scale biological data
• Prior experience working in a matrixed biotechnology or pharmaceutical setting
• Proficiency in R and Python programming, with familiarity in various principles for data manipulation and visualization
• Familiarity with agentic frameworks and the ability to build agents for day‑to‑day tasks that can be automated
• Strong understanding of platforms used in clinical biomarker research, including pathomics, cytomics, immunoassays, mass‑spectrometry, other metabolomics platforms, next‑generation sequencing (NGS), and proteomics
• Knowledge of inflammatory, cardiovascular and metabolic diseases and how computational biology can drive drug discovery and development in these areas
• Ability to translate biological and medical questions into analytical models providing actionable results
• Excellent written and oral communication skills with the ability to present complex data analyses in diverse settings, including cross‑functional team meetings, external collaborations, and scientific publications
• Strong project management skills and organizational awareness, self‑motivation, independence, and leadership.