Real World Analytics Data Scientist
Passionate about making a difference in the world of data-driven precision medicine?
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 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 data scientist with extensive experience and interest in oncology and/or pharmacology. Top candidates will also have experience working with clinical and research data pipelines, working on cross-functional teams, and implementing machine learning and/or statistical models.
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.
Requirements:
- Advanced degree (Masters or PhD) in biostatistics, bioinformatics, immunology, computational biology, statistics, computer science, or related field, or 3+ years experience working with genomic and clinical data in cancer
- Experience working with statistical modeling, data mining and/or machine learning methods
- Proficiency in R or python and/or other programming languages
- 2+ years experience working with clinical cancer data (progression free vs overall survival, clinical trial design, data imputation and managing missing variable bias, etc)
- 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:
- 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)