Scientist, Statistical & Clinical Genetics

Job Description

About This Role

The Clinical Genetics team sits within the Genomic Medicine group in Translational Medicine at Biogen.  Clinical Genetics team members are embedded within and provide support to Biogen’s exploratory, pre-clinical, and clinical pipeline programs, particularly those addressing rare, Mendelian disorders or genetically-defined subsets of common, complex diseases. 

We seek a highly collaborative statistical geneticist or genetic epidemiologist with strong communication skills to join Biogen’s Clinical Genetics team as a Scientist. The Scientist will provide genetics, genomics, and analytical support across the R&D organization, leveraging genomic and phenotypic data from internal and external sources including population-scale human cohorts, disease-specific cohorts, pre-competitive consortia, biobanks, real world data sources, natural history studies, and internal clinical trials.

The Scientist will be deeply involved in one or more therapeutic areas, providing human genetics expertise to help identify, validate, and prioritize novel drug targets, to further our understanding of targets and indications of interest, and to advance pipeline programs.  They will partner with therapeutic area scientists, clinical and biomarker researchers, and operational teams to identify the most promising opportunities for genetics to make a difference to the success or failure of emerging and approved therapeutics.  The successful candidate will have a track record of handling and interpreting large and complex genomic and phenotypic datasets generated as part of clinical trials or in research or diagnostic settings.

What You’ll Do

In this role, you will use internal and external data sources to derive scientific insights and support data-driven decision-making across R&D. You will work independently and within cross-disciplinary teams to design and execute analytical strategies leveraging genomic and phenotypic data to address critical questions in Biogen’s therapeutic areas of interest.  In this role, you will:

• Be the genetics lead on one or more exploratory, pre-clinical and/or clinical pipeline program(s)
• Apply statistical and data visualization approaches to glean and convey insights from complex data
• Keep abreast of, and apply, state-of-the-art methods in statistical genetics
• Perform GWAS, pheWAS, rare variant analysis, polygenic risk score analysis, and other methods to deepen our understanding of genes and indications of interest   
• Apply post-GWAS approaches (e.g., fine mapping, colocalization, Mendelian randomization) to dissect genomic loci associated with disease risk and/or progression
• Consult with therapeutic area experts and program leads to identify critical questions that can be addressed through analysis of clinical trial and internal experimental data; design and execute analytical strategies to address such questions   
• Identify and explore other internal and external data sources to replicate, inform, and/or enrich exploratory findings
• Collaborate with pipeline program teams to inform Go/No Go decisions
• Communicate findings to technical and non-technical audiences
• Lead and contribute to the design, drafting, and publication of scientific manuscripts
• Present your work at scientific conferences and meetings with collaborators

Qualifications

Who You Are

You are a statistical geneticist or genetic epidemiologist with an interest in applying your skills to drug discovery for common, complex disease.

Required Skills

• PhD in human genetics, statistical genetics, genetic epidemiology, or related field with 0-2 years of experience
• Postdoctoral experience preferred
• Strong foundation in statistics and statistical genetics
• Facility with standard programming languages and tools for genomic and clinical data analysis (e.g., Python, R, plink, etc.)
• Experience analyzing genomic data along with phenotypic data such as fluid or imaging biomarkers, disease-specific clinical rating scale assessments, digital measures, response to treatment, etc. 
• Familiarity with analytical approaches for longitudinal data analysis, time to event analysis, and measures of disease progression
• In-depth working knowledge of analysis of WES, WGS, and array data
• Effective teamwork and communication skills

Preferred Skills

• Experience working with additional data types, including RNA-seq, metabolomic and proteomic data
• Cloud computing expertise
• Strong publication record

Additional Information

Why Biogen?

We are a global team with a commitment to excellence, and a pioneering spirit. As a mid-sized biotechnology company