Who We Are:
Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.
Position Description:
Calico is seeking a Data Scientist/Senior Data Scientist to join the statistical genetics team within the Computational Sciences 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 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. in genetics, statistics, statistical genetics, computational biology, or equivalent
- 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 finemapping, 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 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 able to work onsite at least 4 days a week
The estimated base salary range for this role is $120,000 – $185,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.
