Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
Tempus Insights 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.
We are seeking a highly motivated and capable product development scientist with extensive experience and interest in genomics algorithm development and algorithm validation in clinically regulated environments. This position requires experience with dry lab assay validation, analysis of genomic data, algorithm development and evaluation, and statistical modeling. Top candidates will also have experience deploying and operating bioinformatics algorithms within a clinical setting.
Duties and Responsibilities:
- Validate and implement predictive algorithms which leverage molecular, clinical and imaging data inputs to generate novel insights.
- Conduct thorough dry lab assay validations to ensure that our novel algorithms are performing as expected in a clinical setting
- Collaborate with clinicians and scientists to design and perform analyses on cancer clinical sequencing data in order to improve quality of care.
- 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.
- Advanced degree in Bioinformatics, Cancer Biology, Molecular Biology, Bioengineering, Biochemistry or a related field (PhD preferred)
- Deep understanding of CLIA/CAP validation protocols
- Experience with statistical analysis of next-generation sequencing data
Ideal candidates will possess:
- 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