Genetic Epidemiologist / Statistical Geneticist

5 Prime Sciences, Montréal, QC
5primesciences.com
Work remotely, in or near, Montréal, Canada
Full-time

5 Prime Sciences uses insights from human genetics to accelerate drug development and increase return on investment in the life sciences. Using unique datasets and advanced human genetics analyses, as a spin-out from the Richards Lab at McGill University, 5 Prime has been able to grow rapidly and help large pharmaceutical companies, biotech and venture capital companies.

5 Prime Sciences is seeking a Genetic Epidemiologist or Statistical Geneticist to carry out and interpret results from large-scale genetic data analysis, and assist in the development of analytic workflows. The successful candidate will work with a team of bioinformaticians, clinicians and statistical geneticists at 5 Prime Sciences to develop bespoke genetic epidemiology analyses and run existing workflows that identify novel drug targets and validate them, for our partners in the biotechnology industry.

• Independently perform advanced analyses in genetic epidemiology, including GWAS, ExWAS, PRS, PheWAS, and MR.
• Identify high-quality genetic datasets for analyses.
• Contribute to the harmonisation of genetic datasets obtained from different sources and perform QC on these data.
• Run production-level workflows of various statistical genetics methods using Terra.bio to support target validation.
• Contribute knowledge of genetic epidemiology to improve internal databases and interfaces for rapid retrieval, visualisation and interpretation of analysed genomic data.
• Contribute to documentation of computational pipelines, infrastructure and resources.
• Perform data retrieval and management using Google Cloud Platform, ensuring that data is managed securely and efficiently without loss or corruption.
• Work collaboratively with the Analytics Team to draft reports and prepare slides for client presentations.
• Support the development of robust analytical pipelines and perform code review.

• Ability to work independently with minimal supervision.
• Ability to prioritise multiple tasks under tight deadlines.
• Excellent communication and interpersonal skills.
• PhD in Genetic Epidemiology, Statistical Genetics or related field with expertise in the following areas:
  • Demonstrated exposure to human genomic datasets is required (GWAS, WES, WGS, Mendelian Randomisation, etc.).
  • Experience working with large-scale genomic datasets, e.g. UKBiobank, 1000 Genomes etc.
• Significant bioinformatics experience is required with expertise in the following areas:
  • Experience in running software in a Linux or UNIX-like environment including shell scripting and common command-line tools.
  • Demonstrated proficiency in R is required.
  • Demonstrated proficiency in Python is an asset.
• Expertise in cloud computing and software development is an asset:
  • Working familiarity with cloud computing environments (GCP, AWS, DNANexus, Terra, etc.).
  • Knowledge of software development methodology (version control, testing, documentation).