We are looking for a highly analytical, self-motivated and solution-oriented scientist with a strong background in analyzing large-scale, multi-omic molecular and real-world clinical datasets to join our Discover Data Science team supporting Medical Affairs. In this role, you will work directly with the Tempus Medical Sciences Team and oncology research leaders to understand their goals and translate their scientific questions into insight generation. Your work will directly enhance Tempus’ research capabilities and empower our teams and partners to generate actionable insights for patient care.
Responsibilities:
Lead and contribute to research projects in support of research initiatives within R&D and Medical Affairs, leveraging large-scale real-world clinical and multi-omic molecular data.
Present insights from research studies to external research partners through formal presentations and communicate research findings effectively.
Stay updated on methodological advancements in real-world studies, next generation sequencing (DNA/RNA) and oncology guidelines.
Communicate analytical results, and scientific findings clearly to audiences with varying levels of technical and genomics expertise.
Participate in publications and podium activities.
Required Experience:
3+ years experience in industry or academia, following completion of PhD degree in quantitative NGS-related disciplines (e.g. Computational Biology, Genetics, or similar). Alternatively, a PhD in computational biology with a strong record of multi-omic, high-throughput sequencing data analysis
Computational skills using R and SQL, especially relevant statistical tools and packages.
Experience deriving oncology-specific clinical insights using genomic data and deriving real-world endpoints using time-to-event methodologies within a retrospective database.
Excellent project management skills, with proven ability to collaborate with teams of multi-disciplinary scientists to define and execute analysis plans to address scientific questions using omics datasets (genomics, transcriptomics).
Thrive in a fast-paced environment and willing to shift priorities seamlessly
A collaborative mindset, coupled with a genuine eagerness to learn and a steadfast dedication to maintaining integrity in all endeavors.
Nice to have:
Experience integrating molecular data with real-world evidence and longitudinal clinical outcomes.
Experience with AWS and/or Bigquery and/or Google Cloud Platform (GCP)
Proficiency in machine learning techniques, with a nuanced understanding of the strengths and limitations of various approaches, particularly regarding predictive and prognostic algorithms in medical research.
CHI: $100,000-$160,000 USD
NYC: $115,000-$175,000 USD
The expected salary range above is applicable if the role is performed from Illinois and may vary for other locations (California, Colorado, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
