Note: The job is a remote job and is open to candidates in USA. Tempus AI is dedicated to advancing the healthcare industry through precision medicine and AI technology. The Principal Scientist on the Data Insights and Hypothesis Design team will ensure the scientific coherence of Tempus’ multimodal data platform while bridging complex molecular science and scalable data engineering.
Responsibilities
- Conduct rigorous data evaluations, write technical code (SQL, R, Python), and prototype new data offerings within the Tempus Data Model (TDM). Deliver implementation-ready table and column specifications to seamlessly transition initial concepts into scalable, production-grade offerings
- Translate complex client research objectives across the drug discovery and development lifecycle into actionable clinico-genomic data strategies. Ensure seamless alignment between client hypotheses and Tempus capabilities, effectively matching the right datasets to their specific research needs and guiding how to best leverage them
- Serve as a core scientific authority across the organization. Evaluate datasets, perform User Acceptance Testing (UAT), and build data insight reports and capability demonstrations that empower various teams with scientifically validated evidence
- Support the continuous growth and scaling of Tempus' expanding clinical-genomic footprint across diverse disease domains, with an active focus on neurology and Immunology. Bring a holistic, cross-disciplinary view of human biology to profile and validate terabyte-scale datasets, leveraging a proven track record of scientific agility to seamlessly adapt, uncover novel biological patterns, and extract meaningful findings across varying disease areas
Skills
- PhD in a quantitative, NGS-related discipline (e.g., Computational Biology, Genetics, Bioinformatics, Systems Biology) with 6+ years of industry experience across precision medicine, translational research, scientific product development, or related commercial and operational areas
- Deep expertise in at least one of oncology, neurology, or immunology. Additionally strong, demonstrable experience analyzing large-scale clinico-genomic datasets across multiple disease areas
- Proven experience collaborating directly with data engineering and platform teams to build large-scale relational databases, design advanced SQL data models, and support the robust infrastructure needed to create and deploy massive, production-grade models
- Active, up-to-date expertise with cutting-edge computational modeling, including experience leveraging foundation models, generative AI architectures, and agentic workflows to interpret and navigate complex biological data
- Deep expertise executing multi-omic analyses across a diverse spectrum of high-throughput sequencing applications and biotechnologies, including specialized NGS modalities such as single-cell sequencing, immunomics, metagenomics, and varied sequencing platforms
- Proven experience bringing data to market and translating scientific analyses into production-grade data products or clinical-facing solutions
- Proficiency in Python and/or R for reproducible scientific analysis, workflow development, and data visualization
- Strong cross-functional communication skills with the ability to architect end-to-end execution plans, manage client expectations, and mentor technical peers through structured delegation
Benefits
- Incentive compensation
- Restricted stock units
- Medical and other benefits depending on the position
Company Overview
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