Data Scientist, Statistical Genetics

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job 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 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.

Qualifications

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.