Scientist, Genetic Data and Informatics

Overview

The Alnylam Human Genetics (AHG) team is looking for a bioinformatics scientist to join our Data and Informatics group and contribute directly through hands‑on data engineering and pipeline development. The successful candidate will collaborate with statistical geneticists to support the analysis of genetic data from millions of individuals across multiple biobanks, including UK Biobank, All of Us, Our Future Health, Alliance for Genomic Discovery, Finn Gen, and Helix.

This is an onsite position in Cambridge, MA.

• Collaborate with statistical geneticists to translate research algorithms and analyses into robust, reproducible software and pipelines.
• Develop and maintain bioinformatics pipelines for the intake, harmonization, and quality control of individual-level biobank genomic and health data.
• Develop and maintain statistical genetics pipelines for execution across multiple cloud-based platforms and Trusted Research Environments (TRE).
• Design and implement validation pipelines and quality gates for new datasets.
• Contribute to the design and implementation of integration solutions across TREs and data platforms, ensuring clear data provenance across systems.
• Assist in the formalization and development of phenotyping algorithms for large‑scale analysis and expert phenotype curation.
• Work with our managed infrastructure partner to coordinate engineering tasks.
• Maintain Git repositories, participate in code review, author automated tests, and support CI/CD pipeline development and maintenance.
• Support scientific operations through data management, scripting, automation, and other informatics tasks as needs evolve.

• PhD in Bioinformatics, Computer Science, Statistical Genetics, or related field. Title is commensurate with experience.
• Experience developing robust and reliable scientific software in Python. Familiarity with R is useful to support collaboration with and support for statistical genetics colleagues.
• Hands‑on experience building and executing portable pipelines across cloud environments using standard workflow languages (e.g., CWL, WDL, Nextflow) and containerization (e.g., Docker, Singularity).
• Familiarity with software development best practices, including issue tracking, version control, automated testing, and CI/CD.
• Extensive experience working with biobank‑scale genetic and phenotypic data. Familiarity with OMOP and tools in the OHDSI ecosystem is preferred.
• Demonstrated experience executing genomics pipelines within at least one Trusted Research Environment (e.g., UK Biobank RAP, All of Us Researcher Workbench).
• Familiarity with statistical genetics, including GWAS and RVAS methods (e.g., single‑variant testing, burden tests, SKAT) and relevant software (e.g., REGENIE, PLINK).
• Familiarity with variant‑to‑gene post‑GWAS methods (statistical fine mapping, colocalization, Mendelian Randomization).
• Excellent communication skills; ability to work collaboratively and cross‑functionally.

$ - $

The pay range reflects the full‑time base salary range we expect to pay for this role at the time of posting. Base pay will be determined based on a number of factors including, but not limited to, relevant experience, skills, and education. This role is eligible for an annual short‑term incentive award (e.g., bonus or sales incentive) and an annual long‑term incentive award (e.g., equity).

Alnylam's robust Total Rewards package is designed to support your overall health and well‑being. We offer 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.

Our commitment to your well‑being reflects our belief that caring for our people fuels the impact we create together.

We are the leader in RNAi therapeutics- a revolutionary approach with the potential to transform the lives of people with rare and common diseases. Built on Nobel…