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Principal Scientist – Data Insights & Hypothesis Design

Job in Chicago, Cook County, Illinois, 60290, USA
Listing for: SwiftCruit
Full Time position
Listed on 2026-07-20
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below

Overview

Passionate about precision medicine and advancing the healthcare industry? Tempus' proprietary platform connects an 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.

Principal Scientist – Data Insights & Hypothesis Design

Position Overview

As a Principal Scientist on the Data Insights and Hypothesis Design team, you will ensure the scientific coherence of Tempus’ multimodal data platform while bridging the gap between complex molecular science and scalable data engineering.

This position requires strong computational, statistical, and translational research skills, alongside a deep interest in reproducible science and artificial intelligence. You will serve as a cornerstone for expanding our multi-modal applications beyond our foundational oncology roots, actively spearheading scientific efforts to support emerging, large-scale datasets in neurology (Alzheimer s disease) and Immunology & Inflammation (I&I).

Role Focus & Scientific Impact

In this position, you will act as a highly specialized subject matter expert, anchoring our data strategy with deep domain expertise across multiple therapeutic areas. Your impact will be driven by a balance of hands-on technical execution such as data prototyping and code creation and the strategic delegation of modular tasks to effectively scale projects. While you will work closely with cross-functional teams to support go-to-market strategies with rigorous scientific insights and validation, your primary focus will remain on scientific excellence, enablement, and data integrity.

Key Responsibilities
  • Data Evaluation & Prototyping:
    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.
  • Client Alignment & Scientific Advisory:
    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.
  • Cross-Functional Subject Matter Expertise:
    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.
  • Cross-Domain Data Oversight:
    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.
Qualifications
  • Education & Experience:

    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.
  • Domain Expertise:
    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.
  • Data Engineering & Scale Architecture:
    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.
  • Emerging AI & Foundational Modeling Knowledge:
    Active, up-to-date expertise with cutting-edge computational modeling, including experience leveraging foundation models,…
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