Senior Biostatistician, Medical Affairs

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 Data Analytics (RWDA) 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, capable Senior Biostatistician of Medical Affairs 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.

Responsibilities:

• Collaborate on clinical projects with external academic partners
• Collaborate with internal and external stakeholders in the design, analysis, and  interpretation of clinical real-world studies
• Provide clients with guidance on Tempus data model and perform data support, including but not limited to: answer collaborators’ questions, perform data quality control, select and profile cohorts
• Communicate results and scientific findings on a regular basis, using appropriate communication and visualization tools commonly used for biological research
• Stay current with the latest methodological advances in real-world studies
• This position has the potential to publish abstracts and manuscripts and participate in poster presentations in collaboration with external partners

Required Experience:

• Advanced degree (Master’s or PhD) in Computational Biology, Biostatistics/Statistical Genetics, Bioinformatics, Biomedical Informatics, Biometrics, Data Science for Health or similar with 2+ years of experience working with clinical data
• Biological or medical knowledge e.g., Human Disease, Genetics/Genomics, Molecular Biology, or Immunology
• Strong proficiency in R or Python and/or other programming languages
• Proficiency with statistical modeling methods, including time-to-event analysis (TTE), and methodology expertise with observational datasets preferred
• Strong project management skills: defining research questions, writing scientific roadmaps, tracking progress against those roadmaps, aligning scientific results with business outcomes
• Strong communication and presentation skills
• Able to effectively present research results to study team and other collaborators, including results interpretation and drawing appropriate inferences based on study design/statistical methods as well as assessment of study limitations
• Communicating technical concepts to non-technical audiences
• Collaborative mindset, an eagerness to learn and a high-integrity work ethic
• Experience providing mentorship and/or management to junior colleagues
• Sharp attention to detail and passion for delivering high-quality and timely analytics deliverables

Nice to have:

• Experience in the design and analysis of clinical studies or real-world data studies
• Familiarity with SQL
• Experience in cancer genetics, immunology, or molecular biology
• Experience in extracting meaningful insights from genomics data (RNA/DNA-seq)
• Experience with biomarker identification and characterization
• Client-facing or consulting experience and comfort with presenting results to stakeholders
• Experience doing inferential statistics on observational data
• Experience putting data science workflows into production
• Experience with version control, software testing, GCP technical stack
• Understanding of cancer genomics