Senior Scientist, Statistical Genetics

Alnylam Pharmaceuticals; Cambridge; Hybrid; GBP 60,000 - 100,000; Full time

Job summary

An innovative firm is seeking a Senior Scientist to join their Human Genetics team. This role involves applying human genetics in drug discovery, utilizing large datasets to identify novel drug targets. The successful candidate will conduct in-depth analyses and collaborate with project teams to enhance drug development paths. This hybrid position offers a unique opportunity to transform genetic insights into impactful treatments for patients with limited options. Join a top employer recognized for its commitment to innovation and inclusivity, and contribute to groundbreaking advancements in medicine.

Qualifications

• PhD in statistical genetics or related field with 1-6 years of experience.
• Expertise in managing and analyzing large GWAS and RVAS datasets.
• Knowledge of statistical packages and programming languages like R or Python.

Responsibilities

• Run GWAS and RVAS studies, perform meta-analysis across biobanks.
• Identify novel drug targets for RNAi therapeutics.
• Prepare high-quality scientific manuscripts and presentations.

Skills

Statistical Genetics

GWAS Analysis

Python

R Programming

Data Analysis

Communication Skills

Education

PhD in Statistical Genetics

Tools

PLINK

REGENIE

SKAT

Cloud Computational Environments

Job description

Overview

The Research Department at Alnylam is seeking a passionate and creative Senior Scientist to join the Alnylam Human Genetics (AHG) team and play a leading role in applying human genetics in drug discovery and development. AHG has access to multiple large genetic datasets including UK Biobank, All of Us, Discover Me South Africa, and Our Future Health. Our team is focused on mining genetic data to make new discoveries relevant to drug development. This is an exciting opportunity to transform insights from human genetics into opportunities to help patients that have limited treatment options today. The successful candidate will be part of a team conducting in-depth analyses of human genetic data to 1) fuel our efforts to identify novel drug targets in important disease areas and 2) gain biological insights into targets and drugs we are already pursuing that will enhance the development path of our medicines and enable us to reach more patients.

This position is hybrid and will be primarily located in Cambridge, MA.

Key Responsibilities

* Run GWAS and rare variant association studies (RVAS) at biobank-scale, perform meta-analysis across biobanks, run and interpret post-GWAS analyses (e.g. colocalization with molecular QTLs).
* By integrating these results and complementary biological data, independently identify novel drug targets for RNAi therapeutics.
* Identify and implement the latest statistical and analytical methods to help us make discoveries.
* Work closely with project teams to create focused genetic analyses to interrogate individual targets we are either actively pursuing or considering. Use these analyses to 1) assess genetic support for safety and efficacy of these targets and 2) define patient populations and unmet medical needs and expand indications.
* Develop expertise in genetics relevant to biological areas of interest to Alnylam (e.g. metabolic disease, cardiovascular disease, rare disease).
* Independently manage workload including balancing large-scale projects with time-sensitive requests.
* Prepare, review, and deliver high quality scientific manuscripts and presentations for internal/external use.

Qualifications

* PhD in statistical genetics or related field with 1-6 years of post-graduate experience in mining large population cohort datasets to discover sequence variants associated with disease. Title is commensurate with experience.
* Demonstrated expertise in managing and analyzing large GWAS and/or RVAS with a track record of making novel biological discoveries using these data.
* Knowledge of statistical packages commonly used for GWAS and RVAS (e.g., PLINK, REGENIE, SKAT, etc.). Advanced hands-on knowledge of at least one programming language such as R or Python.
* Experience using cloud computational environments for genomics such as the All of Us Researcher Workbench or those provided by DNA Nexus (e.g., UKB RAP).
* Experience conducting meta-analysis, colocalization, and Mendelian randomization would be an advantage.
* Ability to work independently, excellent communication skills, and a track record of publishing in high impact scientific journals.

About Alnylam:Alnylam Pharmaceuticals (Nasdaq: ALNY) has led the translation of RNA interference (RNAi) into a whole new class of innovative medicines with the potential to transform the lives of people afflicted with rare and more prevalent diseases. Based on Nobel Prize-winning science, RNAi therapeutics represent a powerful, clinically validated approach to treating diseases at their genetic source by "interfering" with mRNA that cause or contribute to disease. Since our founding in 2002, Alnylam has led the RNAi Revolution and continues to turn scientific possibility into reality.

Our culture:Our people-first culture is guided by our core values: fiercely innovative, open culture, purposeful urgency, passion for excellence, and commitment to people, and these values influence how we work and the business decisions we make. Thanks to feedback from our employees over the years, we've been fortunate to be named a top employer around the world. Alnylam is extremely proud to have been recognized as the #1 Large Employer by Boston Globe Top Places to Work in 2023 for the third consecutive year, one of Science Magazine's Top Biopharma Employers, one of America's Most Responsible Companies for 2024 by Newsweek, a Fast Company Best Workplace for Innovators, and a Great Place to Work in Canada, France, Italy, Spain, Switzerland, and UK - among others.

At Alnylam, we commit to an inclusive recruitment process and equal employment opportunity. We are dedicated to building an environment where employees can feel that they belong, can bring their authentic selves to work, and achieve to their full potential. By empowering employees to embrace their unique differences at work, our business grows stronger with advanced and original thinking, allowing us to bring groundbreaking medicines to patients. Qualified applicants will receive consideration for employment without regard to their race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, ethnicity, marital status, protected veteran status, disability, or any other characteristics prohibited by law.

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