Senior/Lead Data Science Engineer

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. In 2020, our team grew rapidly amidst greatly increased demand for client-facing analytical support, and our goals in 2021 are even higher.

We are seeking a highly motivated and capable engineer with data science/analytics experience (or data scientist with strong engineering background) to join our team, building critical technical infrastructure to enable us to scale our existing capabilities and unlock new opportunities. Top candidates will have a strong history of building software that solves problems for analytically-minded users, be strong cross-functional collaborators, and be relentlessly curious and creative about how to unlock the power of huge, complex datasets in the fight against cancer.

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 colleagues will be an incredibly smart, diverse, and collaborative group of data scientists and analysts who help our external partners analyze the Tempus dataset for scientific insights. Your work will enable our team to scale and collaborate in our work, both internally and externally: you’ll standardize analytical code into reusable libraries, maintain and improve existing operational infrastructure, architect scalable solutions to documenting results and inspecting the quality of our data, guide the rest of the team in software-building best practices, and think creatively about what technical solutions will enable our team to continue to scale. 

Requirements:

• Proficiency building and maintaining production software in R and/or python, and experience with SQL
• Masters or PhD in a quantitative discipline (computer science, computational biology, bioinformatics, physics, chemistry, statistics, etc.) or equivalent work experience
• Experience deriving scientific insights from messy, incomplete data
• Strong project management skills: defining priorities, writing product roadmaps, tracking progress against those roadmaps, aligning scientific results with business outcomes
• Collaborative and user-centric mindset, an eagerness to learn and a high integrity work ethic
• Experience coordinating cross-functional technical teams

Nice-to-haves:

• Person management experience
• 2+ years of professional experience in a data science or analytics role
• 2+ years experience working with clinical cancer data (progression free vs overall survival, clinical trial design, data imputation and managing missing variable bias, etc)