Lead Real World Analytics Data Scientist at Tempus
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.
On the Outsights team at Tempus, we are data-savvy scientists helping our partners in the pharmaceutical industry maximize the value they get from our real-world data. We work directly with external scientists and business stakeholders to understand their goals, translate those into scientifically robust hypotheses, and analyze Tempus data to answer their scientific questions.
We are seeking a highly motivated and capable pharmaco-oncology leader with extensive experience and interest in data science. This position requires experience with both clinical and research data workflows. Top candidates will also have experience managing large teams and projects, and demonstrated leadership in advanced statistical analysis or data modeling.
What you’ll do:
As part of the external data science team at Tempus, you’ll be on the front lines of our collaborations with external partners, helping them apply cutting-edge data science techniques to unique cancer datasets. Your work will be part of the foundation of the next layer of research questions: you will be responsible for implementing and/or developing bioinformatics tools to address biological questions that query cancer datasets, and for communicating results and scientific findings on a regular basis, using appropriate communication and visualization tools commonly used in biological research.
- Advanced degree (Masters or PhD) in biostatistics, bioinformatics, immunology, computational biology, statistics, computer science, or related field, or 5+ years experience working with genomic and clinical data in cancer
- Demonstrated expertise and/or peer-reviewed contributions to statistical modeling, data mining and/or machine learning
- Fluency in R or python and/or other programming languages
- 5+ years experience working with clinical cancer data (progression free vs overall survival, clinical trial design, data imputation and managing missing variable bias, etc)
- Excellent 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
- Experience managing and mentoring direct reports and cross-functional teams
- Familiarity with standard bioinformatics pipelines
- Familiarity with the oncology pharmaceutical landscape
- Experience doing inferential statistics on observational data
- Experience putting data science workflows into production
- Experience with version control, software testing, AWS technical stack
- External outreach or education (consulting, giving talks, teaching, open source contributions)