Principal/Senior Bioinformatics Validation Scientist job with Tempus Labs

We are seeking a highly motivated and capable senior bioinformatics scientist with extensive experience and interest in translational cancer research and genomics algorithm development. This position requires experience with scientific programming, relational data systems, algorithm development, and statistical modeling. Top candidates will also have experience deploying bioinformatics code within a clinical setting. Tempus Algos is our business to develop, validate and launch new predictive tests, in oncology and new disease areas, by leveraging our clinical + molecular + imaging data to provide novel insights to clinicians and patients.

Duties and Responsibilities:

-Design, execute, and document validation studies for predictive algorithms which leverage molecular, clinical, and imaging data inputs to generate novel insights.

-Standardize validation protocols

-Translate insights from model systems into predictors and classifiers of therapeutic response and prognosis in clinical cancer care.

-Collaborate with scientists and clinicians to design and perform analyses on clinical molecular data in order to improve quality of care.

-Work in interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for our clients.

-Produce high quality and detailed documentation for all projects.

-Develop and implement rigorous testing and validation infrastructure to support the use of predictive algorithms in clinical care.

Required Experience:

-Ph.D. in Cancer Biology, Molecular Biology or a related field

-Computational skills using Python and R.

-Understanding of CLIA/CAP validation protocols and how to bring scientific ideas to market

Ideal candidates will possess:

-Experience in cancer genetics, immunology, or molecular biology

-Experience working with next-generation sequencing data

-Self-driven and works well in interdisciplinary teams

-Experience with communicating insights and presenting concepts to a diverse audience

-Demonstrated programming ability

-Background in predictive or prognostic algorithm development

-Strong background in the development of statistical models

-Collaborative mindset, an eagerness to learn and a high integrity work ethic

Nice to have:

-Experience working with gene expression data

-Experience or familiarity with variant calling methods and/or interpretation

-Experience working with clinical cancer data (progression free vs overall survival, missing data etc)

-Experience with version control and software testing

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