Data Scientist/Senior Data Scientist, Statistical Genetics

Key Skills

C++, Continuous Integration & Continuous Delivery - CI/CD, Data Analysis, Data science techniques, Effective communication skills, Genetics, Julia, MATLAB Programming, Presentation skills, Python Programming, R Programming, SQL

Job Description

Calico is seeking a (Senior) Data Scientist to join the statistical genetics team within the Data Science group. In this position you will develop and apply cutting-edge computational methods to analyze unique biobank-scale datasets (e.g. UK Biobank) to identify potential drug targets for age-related disease. Two major areas of focus will be analysis of longitudinal datasets to identify factors modulating the trajectory of age-related decline, and the analysis of high-dimensional phenotypes. The successful candidate will join a vibrant research community and work closely with internal and external scientific collaborators, and will be expected to contribute to the design of target discovery or validation efforts.

Position Responsibilities:

• Develop and/or apply computational methods suitable for biobank-scale complex or high-dimensional phenotypic datasets from both public and proprietary data sources
• Conceive, design, and execute studies to interrogate the genetic basis of age-related complex traits and of aging trajectories in large human cohorts
• Integrate multiple data sources (e.g. clinical data, genetics, ‘omics) to develop therapeutic hypotheses for age-related disease
• Contribute to software and/or workflows for the analysis of cohort data across multiple research projects and development programs
• Collaborate with and communicate findings effectively to researchers from a broad range of scientific backgrounds, both internally and externally

Position Requirements:

• Ph.D (or equivalent experience). in genetics, statistics, statistical genetics, computational biology, or equivalent; postdoc or industry experience (2+ years) a plus
• Track record of developing and applying new computational and statistical methods tailored to analyzing novel datasets
• Experience with the statistical genetic toolkit for complex traits (e.g. GWAS, gene burden tests, statistical fine-mapping, LD score regression, eQTL/pQTL mapping, colocalization, polygenic risk scores, Mendelian randomization), including methods for ancestrally diverse populations
• Experience with analyzing large, high-dimensional clinical and/or molecular datasets (for example imaging, genomics and other ‘omics, longitudinal data). Familiarity with image analysis and/or physiological modeling is a plus
• Familiarity with large human cohort studies (e.g. UK Biobank, FinnGen, All of Us)
• Strong coding skills in Python and/or R, including experience developing software and/or workflows that can be readily used by others
• Strong interpersonal, written, and verbal communication skills, including collaborating with stakeholders from different scientific disciplines
• Must be willing to work onsite currently at least three days a week

The estimated base salary range for this role is $120,000 - $172,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.