Senior Data Scientist, RWE

Are you 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, delivering crucial information about the right treatments for the right patients, at the right time. The Real World Evidence team at Tempus partners with external pharmaceutical, biotech and academic institutions to offer the best in class data, analysis and methodological guidance to Tempus's real-world data offerings. We are looking for a highly motivated and competent Data Scientist with extensive experience and interest in the design and analysis of pharmacoepidemiological studies to join our team. Responsibilities: - Take part in clinical projects with external Pharma, academic and other partners - Represent the Real World Evidence function and collaborate with internal and external stakeholders in the design, analysis, interpretation and publication of clinical real-world studies - Work on complex problems, and use judgement in selecting and adapting methods as needed - Collaborate with interdisciplinary teams of scientists, engineers, and product developers to convert research into clinically actionable insights for our clients - Stay up-to-date with the latest methodological advances in real-world studies - Build infrastructure including reusable code - Comply with all applicable regulations and Company procedures Required Experience: - An advanced degree (Masters with 4+ years of experience or PhD) or a Bachelor's degree with 6+ years of experience in data science, bioinformatics, biostatistics, epidemiology, immunology, public health, or related fields. - Computational skills using Python, R or SAS and SQL, especially relevant statistical tools and packages Ideal Candidates Will Possess: - Strong data manipulation and analysis skills - Capability to handle large, ambiguous problems - Excellent communication and presentation skills - Self-starter attitude - Understanding of machine learning techniques and the pros and cons of different approaches, particularly regarding predictive and prognostic algorithms in medical research - Experience in cancer genetics, immunology, or molecular biology - Self-driven and cooperative approach, with a motivation to learn and a high-integrity work ethic - Close attention to detail and passion for delivering high-quality and timely analytics deliverables - Ability to effectively present research results to study team and other collaborators, including interpreting results and drawing appropriate inferences based on study design/statistical methods as well as assessing study limitations Nice to Have: - Experience with version control and software testing - Experience with time-to-event analysis and methodology - Experience in oncology Phase II-IV clinical trials and/or experience with the analysis of RWD studies (e.g. using claims, EHR or registry data sources) - Practical experience in helping prepare regulatory submissions to the FDA - Experience supporting data science teams in model building and validation - Client-facing or consulting experience and comfort presenting results to stakeholders #LI-GL1 We are an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.