Data Scientist, Computational Biology
South San Francisco, CA
Applications have closed
Verily
Verily is an Alphabet precision health company that helps pharma and consumer health companies develop safe, effective treatments faster and enable patients, providers and payors to make better care decisionsVerily is an Alphabet company combining a data-driven, people-first approach to bring the promise of precision health to everyone, every day.
Our team combines expertise in healthcare, data science and technology to improve the health and well-being of our communities. We are developing the infrastructure and solutions to harness the profusion of health information for good. Our data-driven solutions span three primary areas: research, care and innovation. Programs include Project Baseline - our research initiative to increase participation and evidence generation in clinical research; Onduo - our personalized virtual care platform, which includes connected tools, lifestyle coaching and clinical support; and Debug - our effort to reduce the threat of mosquito-borne diseases by combining machine learning with sterile insect technique. We’re also actively working to combat the spread of COVID-19 through new programs like Healthy at Work.
Description
As a Data Scientist working on computational biology, you will be joining a team making use of diverse ‘omics data to improve biomarker and target discovery in different disease settings. You will work in a collaborative, cross-functional team to apply molecular platforms in clinical and research settings. You will lead analyses of large, disease-focused datasets to develop new hypotheses about complex disease and develop an analytical story supporting these hypotheses. You will develop new methods and models to help derive insights from our proprietary platforms. You may also work with internal and external collaborators to design new studies in which to apply these molecular platforms and analyses.
Responsibilities
- Develop methods to process, analyze and integrate ‘omic data to derive disease-related insights.
- Analyze complex ‘omics and multi-omics data sets in combination with clinical and other data.
- Build and evaluate predictive models of disease/risk.
- Communicate technical results to internal and external cross-functional teams.
Qualifications
Minimum qualifications:- Advanced degree (Masters or PhD) in a quantitative discipline (Computational Biology, Bioinformatics, Statistics, Computer Science, or related), or equivalent practical experience.
- Proficient in Python and/or R.
- Expertise in statistical data analysis, modeling, machine learning and exploratory data analysis.
- Demonstrated track record of analyzing large biological data sets in translational research settings.
- 1+ years industry experience.
- Experience working with clinical study data in any disease setting.
- Experience working with genomic and/or epigenomic data.
- Outstanding oral and written communication and teamwork.
- Desire to work closely with cross-functional collaborators to help drive the team to results.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Biology Computer Science Data analysis EDA Machine Learning PhD Python R Research Statistics
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