Translational Bioinformatics Scientist
Who we are:
Calico is a research and development company whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan. We will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Executing on this mission will require an unprecedented level of interdisciplinary effort and a long-term focus for which funding is already in place.
Biology is rapidly becoming a data science due to the exponential growth of accessible high-quality biological and medical data. These data are transforming our understanding of biology and disease. Yet deriving valuable scientific insights requires careful analysis and interpretation performed in close collaboration with computational and life scientists. Calico is seeking to expand our group of Data Scientists who are exploring diverse questions from a computational perspective and who are developing new methods to facilitate a deeper understanding of data.
In this role you will work closely with translational scientists, external partners and collaborators to advance Calico’s translational programs. Our programs target fundamental biological processes, informed by aging biology, whose dysregulation may contribute pleiotropically to multiple diseases. To identify diseases where these target processes are dysregulated, we interrogate diseases of aging and their associated drivers, including:
- Cardiovascular disease
- Metabolic & mitochondrial diseases
- Genetic and environmental risk
- Interface with translational scientists in both the Research and Drug Development organizations to identify evidence needed for research and clinical development purposes. Recommend experimental strategies and appropriate designs to gather such evidence. Interpret experimental findings both as an individual contributor and subject-matter expert in data and disease.
- Work with other data scientists and engineers on the Computing team to develop data-driven approaches for making translational development decisions.
- Explore high-dimensional phenotypic data (genomics, transcriptomics, metabolomics, proteomics, and imaging, across multiple experimental conditions) to better understand disease biology and how these pathologies interact with our developing therapeutics. This will involve translating insights across disease datasets including between meta-analyses of public data, cell culture models, mouse models and early stage human research.
- Assist biomarker teams to develop and quantify phenotypic signatures that capture either the state of a disease or target engagement for programs that are advancing towards the clinic.
- Communicate clearly and effectively in verbal, visual, and written form to stakeholders with varying levels of technical knowledge.
- Ph.D. in a quantitative field such as Bioinformatics, Computational Biology, Statistics, Biological Sciences, Genetics, Genomics, Computer Science, or equivalent preparation and experience.
- 3+ years of work experience in the pharmaceutical, biotech or healthcare industry.
- 6+ years of demonstrated experience analyzing biological data.
- Expertise in at least two of the disease areas stated above.
- Experience with testing statistical hypotheses using high-dimensional genomic data (e.g., bulk RNAseq, single-cell RNAseq, ribosome profiling, ATACseq/ChipSeq, metabolomics, proteomics, imaging).
- Fluent in R and/or Python with experience using industrial best practice (version control, unit testing, and package management).
- Experience in applying statistical methods, such as: generalized linear models, hazard models, maximum likelihood estimation, and false discovery rate control.
- Track record of effective cross-functional collaboration.