Senior Data Scientist, Outcomes Research

🕒 April 30

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Logo of Tempus AI

Tempus AI

1001 - 5000 employees

Founded 2015

🧬 Biotechnology

🤖 Artificial Intelligence

Healthcare • Biotechnology • Artificial Intelligence

Tempus AI is an advanced healthcare technology company that specializes in precision medicine through the use of AI and genomic profiling. The company provides innovative solutions across various medical fields, including oncology, cardiology, neurology, and psychiatry. Tempus enables healthcare providers to make informed treatment decisions by integrating real-world data, clinical trial matching, and algorithmic testing to improve patient outcomes and accelerate drug development.

📋 Description

• Lead and execute HEOR and RWE projects (e.g., outcomes analysis, treatment patterns, and healthcare resource utilization) with external Pharma, academic, and other partners. • Represent the Outcomes Research function and collaborate with internal and external stakeholders in the design, analysis, interpretation, and publication of real-world studies. • Work on complex problems, exercising judgment in selecting and adapting appropriate epidemiologic and health economic methodologies. • Work with interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for our clients. • Stay current with the latest methodological advances in real world studies. • Build infrastructure including reusable code. • Comply with all applicable regulations and Company procedures.

🎯 Requirements

• Advanced degree (Masters with 5+ years of experience or PhD with 3+ years of experience) or Bachelor’s degree with 8+ years of experience in data science, bioinformatics, biostatistics, epidemiology, public health, or related fields. • Computational skills using R and SQL, specifically applied to large-scale healthcare datasets. • Strong data manipulation and analysis skills tailored to observational data. • Deep familiarity with HEOR and RWE methodologies, including techniques to address confounding (e.g., propensity score matching, inverse probability weighting). • Experience analyzing large, complex real-world datasets, including administrative claims, electronic health records (EHR), and clinico-genomic databases. • Strong communication and presentation skills, with the ability to effectively translate complex methodologies to non-technical stakeholders. • Self-driven mindset with the ability to tackle ambiguous problems and work well in interdisciplinary teams. • Experience with time-to-event analysis and survival methodology. • Experience working in oncology and/or analyzing outcomes specific to cancer genetics, immunology, or molecular biology. • Collaborative approach, an eagerness to learn, and a high-integrity work ethic. • Sharp attention to detail and passion for delivering high-quality, timely analytics. • Ability to draw appropriate inferences based on study design and explicitly assess and communicate study limitations.

🏖️ Benefits

• incentive compensation • restricted stock units • medical and other benefits

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