Senior Scientist, Statistical Genetics

Alnylam Pharmaceuticals•Cambridge, MA

4d•Onsite

About The Position

The Alnylam Human Genetics (AHG) team is looking for a passionate and driven scientist to apply human genetics to drug discovery and development. The successful candidate will perform comprehensive analyses of human genetic data to uncover new therapeutic targets, with a focus on specific disease areas of interest. AHG has access to large genetic data from millions of individuals across multiple biobanks, including UK Biobank, All of Us, Discover Me South Africa, Our Future Health, and the Alliance for Genomic Discovery. This is an exciting opportunity to transform insights from human genetics into opportunities to help patients that have limited treatment options today. This position is onsite five days a week and will be primarily located in Cambridge, MA.

Requirements

PhD in Statistical Genetics or a related field 3+ 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 at least one therapeutic area (e.g., metabolic disease, cardiovascular disease, neurological disorders, rare disease) 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, etc.) and strong hands-on skills in R and Linux command line
Experience working in cloud computational environments for genomics such as the (e.g., UKB RAP, All of Us Researcher Workbench, ICA).
Independent, detail-orientated scientist with excellent communication skills and a record of publishing impactful research

Responsibilities

Apply human genetics (common and rare genetic association studies) using biobank-scale data (e.g., UK Biobank, All of Us, Our Future Health, Alliance for Genomic Discovery) with the aim of finding new targets for RNAi therapeutics.
Perform biobank-scale association analyses, conduct meta-analyses across diverse cohorts, including leveraging publicly available summary statistics, and integrate findings with molecular QTLs and other omics data to strength hypotheses.
Perform post-GWAS analyses aimed at identifying causal genes and potential therapeutic targets (e.g., fine-mapping, colocalization, Mendelian Randomization)
Lead target finding and validation efforts in at least one therapeutic area of interest to Alnylam (e.g., metabolic disease, cardiovascular disease, neurological disorders, rare disease)
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

Benefits

comprehensive benefits including medical, dental, and vision coverage, life and disability insurance, a lifestyle reimbursement program, flexible spending and health savings accounts and a 401(k)with a generous company match
Eligible employees enjoy paid time off, wellness days, holidays, and two company-wide recharge breaks.
We also offer generous family resources and leave.

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