Senior Scientist, Statistical Genetics
Alnylam Pharmaceuticals
August 08, 2026
On-site
Cambridge, MA
Clinical Research and Development
Key Responsibilities:
- Perform common and rare variant association studies, including large-scale “all-by-all” analyses, using biobank-scale data to identify and prioritize novel RNAi therapeutics targets.
- Lead cross-biobank meta-analyses integrating internal and publicly available summary statistics to maximize power, replication, and trans-ancestry discovery.
- Implement post-GWAS methods to nominate causal genes and therapeutic hypotheses (fine-mapping, colocalization, Mendelian randomization, functional annotation integration).
- Drive methodological innovation (multi-omics integration, polygenic modeling, rare variant aggregation, AI/ML-enabled prioritization).
- Establish best practices for data organization, knowledge management, and results dissemination.
- Increase external visibility via high-impact publications, conference presentations, and collaborations.
Qualifications:
- PhD in Statistical Genetics or related field with 3+ years relevant postdoctoral/industry experience.
- Expertise in statistical genetics (GWAS/RVAS; single-variant testing, burden tests, SKAT) and software such as REGENIE, PLINK.
- Experience analyzing individual-level biobank-scale genetic and phenotypic data with a track record of novel discoveries.
- Experience with multi-biobank analyses/meta-analyses (METAL, RAREMETAL, REMETA), including sample overlap handling.
- Variant-to-gene post-GWAS expertise (fine-mapping, colocalization, Mendelian randomization).
- Experience with multi-ancestry data and population-enriched variant discovery.
- Experience with scalable tools for multivariate, time-to-event, and longitudinal analyses.
- QC experience on biobank-scale genetic data (WGS/WES/imputed).
- Phenotype generation and cross-biobank curation/harmonization.
- Proficiency in Linux; hands-on Python and R.
- Cloud genomics workflow experience (DNAnexus, All of Us Researcher Workbench, Terra).
- Strong communication, collaboration, and high-impact publication record.
Pay/Benefits:
- U.S. pay range: $126,400.00–$189,600.00 base salary; eligible for annual short-term incentive and annual long-term incentive.
- Benefits include medical/dental/vision, life/disability insurance, lifestyle reimbursement, flexible spending/HSAs, 401(k) with match, paid time off, wellness days, holidays, and recharge breaks.
Location:
- Onsite; primarily Cambridge, MA.
- Perform common and rare variant association studies, including large-scale “all-by-all” analyses, using biobank-scale data to identify and prioritize novel RNAi therapeutics targets.
- Lead cross-biobank meta-analyses integrating internal and publicly available summary statistics to maximize power, replication, and trans-ancestry discovery.
- Implement post-GWAS methods to nominate causal genes and therapeutic hypotheses (fine-mapping, colocalization, Mendelian randomization, functional annotation integration).
- Drive methodological innovation (multi-omics integration, polygenic modeling, rare variant aggregation, AI/ML-enabled prioritization).
- Establish best practices for data organization, knowledge management, and results dissemination.
- Increase external visibility via high-impact publications, conference presentations, and collaborations.
Qualifications:
- PhD in Statistical Genetics or related field with 3+ years relevant postdoctoral/industry experience.
- Expertise in statistical genetics (GWAS/RVAS; single-variant testing, burden tests, SKAT) and software such as REGENIE, PLINK.
- Experience analyzing individual-level biobank-scale genetic and phenotypic data with a track record of novel discoveries.
- Experience with multi-biobank analyses/meta-analyses (METAL, RAREMETAL, REMETA), including sample overlap handling.
- Variant-to-gene post-GWAS expertise (fine-mapping, colocalization, Mendelian randomization).
- Experience with multi-ancestry data and population-enriched variant discovery.
- Experience with scalable tools for multivariate, time-to-event, and longitudinal analyses.
- QC experience on biobank-scale genetic data (WGS/WES/imputed).
- Phenotype generation and cross-biobank curation/harmonization.
- Proficiency in Linux; hands-on Python and R.
- Cloud genomics workflow experience (DNAnexus, All of Us Researcher Workbench, Terra).
- Strong communication, collaboration, and high-impact publication record.
Pay/Benefits:
- U.S. pay range: $126,400.00–$189,600.00 base salary; eligible for annual short-term incentive and annual long-term incentive.
- Benefits include medical/dental/vision, life/disability insurance, lifestyle reimbursement, flexible spending/HSAs, 401(k) with match, paid time off, wellness days, holidays, and recharge breaks.
Location:
- Onsite; primarily Cambridge, MA.