Associate Director of Phenomics

Role Summary

Location: USA – Pennsylvania (Upper Providence) and UK – Hertfordshire (Stevenage). We are seeking an Associate Director of Phenomics with extensive experience in epidemiology, real-world data (RWD), and biostatistics to apply these skills to large, diverse health cohorts linked to genetics and other -omics to support drug discovery and development. The role will lead the development of novel phenotypes describing disease severity, disease progression, sub-populations, biomarker trajectories, and other advanced health outcomes, and will guide cross-functional teams in applying these methods across data sources. The successful candidate will communicate findings to stakeholders and drive innovation by integrating deep, longitudinal EHR data with genetic and genomic data.

Responsibilities

• Leverage longitudinal, RWD and other observational data derived from large, diverse human cohorts linked to genetics and other -omics to create novel, advanced phenotypes that describe disease severity, disease progression, disease sub-populations, biomarker trajectories, and more advanced health outcomes
• Proactively lead the design, delivery, and communication of custom analyses requiring advanced epidemiologic and/or statistical approaches to answer challenging scientific questions required for business development, portfolio decisions, or other GSK-critical requests where the integration of RWD with -omic data is an important component.
• Advance novel methods (e.g. AI/ML, mediation, interaction, other prediction, …) that improve our ability to develop novel phenotypes and analyses (as described above).
• Identify and communicate the strengths, limitations, confounders, and potential biases for any downstream genetic or other -omic analyses that leverage inputs derived from RWD or other observational data.

Qualifications

• Required: Advanced degree (PhD or equivalent) in a relevant scientific discipline.
• Required: Five or more years of experience in innovation and application of real-world data (RWD) and other observational data from large cohorts to answer diverse scientific questions across therapeutic areas.
• Required: Five or more years of experience in performing a range of statistical approaches supporting the analyses of identifying analytic cohorts, defining exposures, and measuring associations against diverse types of exposures and outcomes.
• Required: Three or more years of experience of delivering novel and impactful insights from complex EHR data individually, or through leadership of a team.
• Required: Three or more years of experience in R programming
• Required: Three or more years of experience in Epidemiology and causal inference; demonstrated ability to apply advanced Epidemiology / causal inference to diverse datasets; and communicate methods and findings to a broad set of stakeholders.
• Preferred: Hands-on experience integrating RWD with proteomic and/or other genetic & genomic data in biobank-scale cohorts.
• Preferred: Strong leadership, collaboration and partnership skills to work effectively with cross-functional teams.
• Preferred: Excellent communication and presentation skills (including the appropriate generation of figures and tables to visualise results) to convey findings and recommendations to stakeholders.
• Preferred: Ability to identify strengths, limitations, potential confounders and bias from the use of RWD and other observational data; and develop/implement strategies to address these issues.
• Preferred: Proven project leadership / management for small teams with a focus on data quality, delivering results, and communication to diverse stakeholders.
• Preferred: Excellent problem-solving and analytical skills to address complex scientific questions.