Senior Data Scientist

About the position

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. The Data Science Operations team at Tempus collaborates with data scientists, engineers, and biostatisticians to enhance longitudinal clinical data for Tempus’s real-world data offering. We are seeking a solution-oriented Senior Data Scientist passionate about bringing high quality real world data to internal researchers and external teams at top Pharmaceutical and Life Science companies, all in pursuit of improving oncology patient care with one of the largest molecular and clinical databases of cancer patients in the world.

Responsibilities

• Become an expert in Tempus longitudinal clinical data and patient tokenization to link third party datasets to Tempus’s real world data ecosystem
• Design and execute concordance analyses and reliability studies to demonstrate the validity of real-world datasets, ensuring results meet standards for publication in scientific journals
• Develop new methodologies for harmonizing and integrating various clinical data streams (e.g., EHR, claims, mortality data) to enhance the comprehensiveness and accuracy of clinical datasets
• Partner with internal stakeholder teams, including Outcomes Research, Engineering, Applied AI, Data Science, and others, to identify and implement enhancements to our data offering to meet diverse use cases
• Expand our automated data testing suite to proactively identify and address data regressions
• Provide subject matter expertise to internal technical and non-technical audiences, ensuring that methods and results are clearly understood and trusted

Requirements

• Bachelor’s degree in the natural sciences or a quantitative/computational discipline (e.g., Statistics, Epidemiology, Informatics, Computer Science, Economics) with 3-5 years of work experience in data science or a related field. Alternatively, Master’s degree with 2-3 years of work experience.
• Exceptional data exploration and debugging skills using SQL and either R or Python, with the ability to identify, diagnose, and resolve data issues efficiently
• Eagerness to learn and develop expertise across interdisciplinary fields, including real world clinical data, hypothesis testing, time to event analysis, and generative AI.
• Excellent technical communication skills, including spoken and written communication, as well as the ability to create effective visuals to convey complex technical concepts
• Track record of successfully working cross functionally to execute complex projects with multiple cross-functional stakeholders
• Ability to translate domain knowledge into testable data expectations
• Experience with engineering practices for research computing, including version control (Git/GitHub), code review, and cloud computing
• A habit of self-directed learning through peers, documentation, scientific literature, and hands-on involvement in diverse projects.

Nice-to-haves

• Hands-on experience working with real-world data, including administrative claims, electronic health records (EHR), or registry data.
• Experience with observational study design, hypothesis testing, and time to event analysis
• Strong organizational skills, with the ability to break down complex tasks into manageable subcomponents and effectively address each part while maintaining a focus on overall project goals
• Ability to understand complex systems end-to-end and anticipate the consequences of specific design choices as they propagate throughout that system
• Experience with test driven development and/or automated data testing through dbt (data build tool).
• Experience with Bigquery and/or Google Cloud Platform (GCP)
• Thrive in a fast-paced environment and be willing to shift priorities seamlessly
• Goal orientation, self-motivation, strong sense of ownership, and drive to make a positive impact in healthcare.

Benefits

• Incentive compensation
• Restricted stock units
• Medical and other benefits