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.
The Real World Evidence (RWE) group within the Pharma R&D team at Tempus works with pharmaceutical partners to provide best-in-class data, analysis, and methodological guidance to Tempus’s real-world data offering. We are seeking a highly motivated and solutions-oriented RWE Data Scientist with experience and interest in oncology and clinical/epidemiological study design and execution to join our team. Top candidates will have experience working with clinical and research data pipelines, and/or performing biostatistical, epidemiological, or real-world data analytics on observational healthcare data.
Responsibilities:
- Lead independent analysis of Tempus data for RWE studies with large Pharma partners
- Perform extensive coding and derive real-world endpoints, exhibiting deep comprehension of Tempus molecular and clinical data
- Interpret results of RWE analyses to draw appropriate inferences based on study design/statistical methods, while also evaluating study limitations.
- Communicate research findings effectively to the external Pharma partner’s RWE and clinical teams, providing strategic recommendations.
- Collaborate with internal product, engineering, oncology, bioinformatics, and clinical abstraction teams to continually enhance Tempus data quality, products and analytical best practices.
- Stay updated on methodological advancements in real-world studies, oncology guidelines (NCCN and ongoing clinical trials) and their alignment to the evolving oncology landscape within Tempus’ database.
- Ensure compliance with all relevant regulations and company procedures.
Qualifications:
- Master’s degree in epidemiology, biostatistics, data science, public health, or related fields
- 1+ years of work experience with observational real-world healthcare data, including analytical experience with time-to-event methodologies
- Proficient in using R and SQL, especially statistical tools and packages
- Demonstrated experience interfacing with clients, showcasing adeptness in presenting and tailoring messaging to a variety of stakeholders
- Excellent project management skills, with proven ability to collaborate with teams of multi-disciplinary scientists to define and execute analysis plans
- Proficient in navigating large, complex problems within a fast-paced environment
- Excellent written and oral communication skills
- Excellent presentation and interpersonal skills
Nice to have:
- Prior involvement in oncology Phase II-IV clinical trials or proven expertise in analyzing RWD studies, including utilization of claims, EHR, or registry data
- Experience deriving oncology-specific clinical insights using genomic data and deriving real-world endpoints using time-to-event methodologies within a retrospective database
- Experience with AWS and/or Bigquery and/or Google Cloud Platform (GCP)
- Experience producing code in a collaborative environment, using Git, GitHub, and code reviews
- A collaborative mindset, coupled with a genuine eagerness to learn and a steadfast dedication to maintaining integrity in all endeavors
- Thrive in a fast-paced environment and demonstrate ability to communicate technical concepts to non-technical stakeholders
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