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 Tempus' Real World Evidence (RWE) team, we work with Key Opinion Leaders in academia and the research community to generate novel insights with real-world data. We work directly with the Tempus Medical Sciences Team and oncology research leaders to understand their goals and translate their scientific questions into exploratory data analyses. We are seeking a highly motivated, capableBiostatistician Iwith 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.ResponsibilitiesCollaborate on projects with external partners, helping them analyze unique cancer datasetsCollaborate with internal and external stakeholders to support the design, analysis, and interpretation of real-world clinical and molecular dataCommunicate results and scientific findings on a regular basis, using appropriate communication and visualization tools commonly used for biological researchStay current with the latest methodological advances in real-world studiesThis position has the potential to publish abstracts and manuscripts and participate in poster presentations in collaboration with external partnersRequired Experience:Bachelor's degree in biostatistics, epidemiology, public health, or a related field with 2+ years of experience working with clinical data,orMaster's degree in biostatistics, epidemiology, HEOR, or a related fieldFamiliarity with statistical modeling methods, and expertise with observational datasets preferredStrong proficiency in R or Python and/or other programming languagesStrong project management skills: defining research questions, writing scientific roadmaps, tracking progress against those roadmaps, aligning scientific results with business outcomesDemonstrated ability to communicate technical concepts to non-technical stakeholdersCollaborative mindset, eagerness to learn, and a high-integrity work ethicNice-to-have:Experience doing inferential statistics on observational dataExperience putting data science workflows into productionExperience with version control, software testing, GCP technical stackUnderstanding of cancer genomics#LI-GL1
