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University of Pennsylvania, Philadelphia, PA, USA

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"Senior Data Scientist - Genetics"

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Senior Data Scientist - Genetics

The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn's distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America's Best Large Employers in 2023.

Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.

The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.

Posted Job Title
Senior Data Scientist - Genetics

Job Description Summary
The UPenn department of genetics is seeking a Senior Data Scientist for clinical genomic pipeline design and implementation.

Job Description
The successful candidate will be working with a broad team of quantitative analysts, including Statisticians, Data Scientists, Clinical and Basic trainees, and other bioinformaticians. Their role will involve developing and implementing new quantitative strategies to improve our understanding and ability to diagnose genetic disorders through a large-scale genomic clinically grade testing. Senior Data Scientists are passionate about applying their knowledge of biology and of methods for molecular, cellular or radiologic data-analysis to uncover general principles of genetic disorders and use these to create clinically useful biomarkers. They will develop, extend and apply computational pipelines for data-analysis to patient cohorts ranging from tens of individuals to hundreds of thousands. These will be executed at scale via distributed software solutions on both local HPC and cloud-based assets. Our datasets comprise petabytes, and are growing rapidly, linked to key clinical endpoints. This requires a strong background in biology to help ensure the right questions are asked, but linked to strong technical and personal communication skills, to help ensure insights are broadly adopted and appropriate analyses are performed. You may work with molecular (WGS, panel-sequencing, RNA-Seq, proteomic) or imaging (digital pathology, radiomic) data, and practical experience in one of these two areas is essential. Beyond your strong inter-personal skills and computer science background, you will have experience with implementation skills at least one of R, Perl or Python. You will be comfortable in UNIX/Linux environments and producing well-documented code. Multi-year experience (>10years) with cloud-computing or HPC is essential.

Master of Science and 1 to 2 years of experience, or an equivalent combination of education and experience required. Ph.D. preferred.

This position is contingent upon grant funding.

Job Location - City, State
Philadelphia, Pennsylvania

Department / School
Perelman School of Medicine

Pay Range
$100,000.00 - $160,000.00 Annual Rate
Salary offers are made based on the candidate's qualifications, experience, skills, and education as they directly relate to the requirements of the position, and in alignment with salary ranges based on external market data for the job's level. Internal organization and peer data at Penn are also considered.

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