Computational Biologist II, Tempus Discover at Tempus AI, New York City, NY

Computational Biologist II, Tempus Discover at Tempus AI in New York City, NY. Full-time. $90,000 to $135,000 a year. Apply with swipeandhired.

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.

Computational Biologist II, Tempus Discover

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.

About this position
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 external research collaborations. 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:

• 1+ 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.
• Experience deriving oncology-specific clinical insights using genomic and/or real-world 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.
• Hands-on experience applying machine learning techniques or foundation models (FMs) to complex biomedical or multi-omic datasets.

CHI: $90,000-$135,000
NYC/SF: $100,000-$150,000
The expected salary range may vary for other locations. 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.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.