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.

With the advent of genomic sequencing, digital imaging, and techniques for large-scale clinical data processing, we have powerful new weapons in the data-driven fight against cancer. We’re on a mission to connect an entire ecosystem to redefine how genomic and clinical data is used for evidence-based medicine.

On the RWDA team at Tempus, we help Key Opinion Leaders in academia and the research community generate novel insights using real world data. We work directly with the Tempus Medical Sciences Team and oncology research leaders to understand their goals, translate those into exploratory data analyses to answer their scientific questions.

We are seeking a highly motivated and capable data analyst with experience and interest in oncology and/or molecular data. Top candidates will also have experience working with clinical and research data pipelines, and/or doing biostatistical, epidemiological, or HEOR research on observational healthcare data.

What you’ll do

As part of the RWDA team at Tempus, you’ll be on the front lines of our collaborations with external partners, helping them analyze unique cancer datasets. Your work will be part of the foundation of the next layer of research questions: you will support analyses on real-world clinical and molecular data, and communication of results and scientific findings on a regular basis, using appropriate communication and visualization tools commonly used in biological research.

Requirements:

• Bachelor’s degree in biostatistics, epidemiology, public health or a related field with at least 2+ years of experience working with clinical data, or a Masters degree in biostatistics, epidemiology, HEOR or a related field
• Familiarity with statistical modeling methods, expertise with observational datasets preferred
• Strong proficiency in R or python and/or other programming languages
• Strong project management skills: defining research questions, writing scientific roadmaps, tracking progress against those roadmaps, aligning scientific results with business outcomes
• Demonstrated ability to communicate technical concepts to non-technical stakeholders
• Collaborative mindset, an eagerness to learn and a high integrity work ethic

Nice-to-have:

• Experience doing inferential statistics on observational data
• Experience putting data science workflows into production
• Experience with version control, software testing, AWS technical stack
• Understanding of cancer genomics

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