Senior Scientist, Statistical Genetics

Role Summary

Senior Scientist, Statistical Genetics will apply human genetics to drug discovery and development, performing comprehensive analyses of genetic data to uncover new therapeutic targets with a focus on neurological and ocular diseases. The role leverages biobank-scale data from UK Biobank, All of Us, Our Future Health, the Alliance for Genomic Discovery, and other biobanks. This onsite position is based in Cambridge, MA.

Responsibilities

• Lead target finding and validation efforts for the neuroscience and ocular therapeutic area.
• Apply human genetics (common and rare genetic association studies) using biobank-scale data with the aim of finding new targets for RNAi therapeutics.
• Perform biobank-scale association analyses, conduct meta-analyses across diverse cohorts, and integrate findings with molecular QTLs and other omics data to strengthen hypotheses.
• Perform post-GWAS analyses aimed at identifying causal genes and potential therapeutic targets (e.g., fine-mapping, colocalization, Mendelian Randomization).
• Create and validate new phenotypes including imaging-based phenotypes.
• Collaborate closely with cross-functional teams to follow-up on promising targets and to deliver genetic analyses that will help inform existing drug development programs.
• Stay at the forefront of statistical and computational genetics methods, implementing innovative approaches that accelerate target discovery and validation.
• Communicate findings effectively through internal presentations, project reports, and/or high-impact publications.

Qualifications

• PhD in Statistical Genetics or a related field; 3–6 years of relevant post-graduate experience applying genetics to drug target discovery. Title is commensurate with experience.
• Demonstrated expertise in GWAS and/or RVAS, meta-analysis, and performing post-GWAS analyses to help elucidate causal mechanisms (e.g., fine-mapping, colocalization, TWAS, Mendelian Randomization, polygenic risk prediction).
• Track record using genetic data to make novel biological insights or find new drug targets.
• Deep knowledge of neurological and/or ocular disorders with the ability to contextualize genetics findings into biological mechanisms and clinical relevance.
• Demonstrated experience collaborating with biologists, disease area experts, and physician scientists to interpret the results of genetic analyses, support disease understanding and prioritize follow-up work.
• Well-versed in leveraging publicly available genetics resources (e.g., OpenTargets, OMIM, GTEx, GWAS catalog).
• Proficiency with statistical genetics tools (e.g., PLINK, REGENIE, SKAT) and strong hands-on skills in R and Linux command line.
• Experience working in cloud computational environments for genomics (e.g., UKB RAP, All of Us Researcher Workbench, ICA).
• Independent, detail-oriented scientist with excellent communication skills and a record of publishing impactful research.