Are you passionate about precision medicine and transforming healthcare?

With recent advances in core technology, AI can now meaningfully support clinical decision-making. Tempus’ proprietary platform links an end-to-end ecosystem of real-world evidence to give physicians timely, practical insights—helping deliver the right information about the right treatments for the right patients, at the right time.

We are looking for an enthusiastic, highly skilled bioinformatics scientist with experience in—and a strong interest in—translational cancer research and clinical genomics. This role requires expertise in scientific programming, relational data systems, algorithm development, and statistical modeling. The strongest candidates will also have experience deploying bioinformatics tools in clinical environments.

Key Responsibilities:
– Develop and improve algorithms to identify cancer variability by analyzing next-generation sequencing data.
– Create and run analyses to assess progress in variant calling, variant classification, data modeling, and analytical systems.
– Convert results from model systems into predictors and classifiers of treatment response and prognosis for clinical cancer care.
– Partner with scientists and clinicians to design and execute analyses using cancer clinical sequencing data to enhance care quality.
– Work with cross-functional teams of scientists, engineers, and product developers to turn research into clinically actionable insights for clients.
– Provide thorough, high-quality documentation for all projects.

Preferred Qualifications:
– A completed Ph.D. in Cancer Biology, Molecular Biology, or a related field.
– Proficiency with computational tools such as R, Bioconductor, and/or Python.

Ideal Candidates Also Have:
– Experience in cancer genetics, immunology, or molecular biology.
– Experience working with next-generation sequencing data.
– Strong self-motivation and the ability to thrive in interdisciplinary teams.
– Experience communicating insights and explaining concepts to a broad range of audiences.
– Background building predictive or prognostic algorithms.