Senior Principal Computational Geneticist

ROLE SUMMARY

Human genetics has established itself as a cornerstone of modern drug discovery, yet we are only beginning to unlock the full potential of the rich biomedical data now being generated.

We are seeking a geneticist with a passion for applying cutting-edge approaches, including genetic epidemiology, quantitative genetics, computational biology, AI, functional omics, epigenetics, and other multi-omics data resources, to accelerate the identification of causal mechanisms, therapeutic indications, biomarkers, and patient stratification strategies.  The ideal candidate will have demonstrated leadership of managing cross-functional teams to integrate multi-modal omics data with biologic information to help drive target identification.

The Integrative Biology team within the Internal Medicine Research Unit works closely with disease area biologists to address unmet medical needs in metabolic diseases, including obesity and cardiovascular disease, with a particular focus on atherosclerotic cardiovascular disease. We do this by developing and applying advanced methods to analyze human genetics and other large-scale molecular datasets.

In addition, we collaborate with AI and machine learning teams to develop methods and tools that enhance our ability to work with and interpret complex genetics and genomics data. These tools help deliver meaningful insights and actionable recommendations to disease area project teams.

The ideal candidate for this role will have experience leading external partnerships, including developing and building external collaborations and managing relationships with external partners to ensure the timely delivery of high-quality genetics and genomics data, and to incorporate results into target identification and validation. 

The applied human genetics scientist position offers an opportunity to execute science-based drug discovery within one of the world’s leading developers of human therapeutics, at Pfizer’s Kendall Square research facility in Cambridge Massachusetts. 

ROLE RESPONSIBILITIES  

• Provide quantitative genetics expertise and conduct analyses to derive impactful results through interactions with biologists within the Internal Medicine Research Unit. 
• Provide expertise and quantitative skills on the application of genetics and functional genomics to inform project teams in: 
• Identification of novel therapeutic targets 
• Review and validation of therapeutic hypotheses 
• Mechanistic understanding of disease pathogenesis and causal pathways 
• Innovative approaches to identifying mechanism related biomarkers via integrating genetics with clinical and 'omic datasets. 
• Identification of potential disease indications. 
• Matching novel therapies to patients with relevant disease sub-types. 
• Develop and lead cross-functional teams in statistics, bioinformatics, computational biology, clinicians to ensure high-quality genetic and ‘omics data is integrated into incorporated into exploratory research. 
• Work with our partners in machine learning and AI to build tools that provide genetics / genomics results to our scientists and other stakeholders. 
• Work in collaboration with research biologists and project teams to identify the best opportunities to translate genetic and related data to inform and prioritize assets in the portfolio; and with clinical teams to inform optimum patient selection, stratification and trial design. 
• Develop and build high-value external collaborations; Manage and maintain internal and external collaborative projects to specified timelines and milestones. 
• Communicate study findings and analyses with internal partners, leadership, administration, and collaborators. 
• Manage, support and promote relationships with the external community that can add value to target selection and validation at Pfizer 
• Willingness to learn new skills and be “change agile” 

BASIC QUALIFICATIONS  

• Background in biological and/or quantitative sciences; PhD required and post-doctoral experience in genetics, statistical genetics, or genetic epidemiology with at least five (5) years relevant experience 
• Sound statistical and quantitative skills, with knowledge of epidemiological principals and population-based research. 
• Experience developing and manag