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Data Scientist, Statistical Genetics

Company: Verily

Location: South San Francisco, CA, United States

Posted on: November 24

Verily 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.


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.


* Develop methods that integrate genomic data with other multi-omic data and publicly available data (e.g. GWAS) to derive disease-related insights.
* Analyze complex 'omics data sets in combination with clinical and other data.
* Build and evaluate models of disease risk.
* Communicate technical results to internal and external cross-functional teams.


Minimum qualifications:

* Advanced degree 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 statistical genetics methods development and application in translational research.

Preferred qualifications:

* 1+ years industry experience.
* Experience working with clinical study data in any disease setting.
* Experience working with single cell 'omics data.
* Outstanding oral and written communication and teamwork.
* Desire to work closely with cross-functional collaborators to help drive the team to results.

Recommended Skills

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