What are the responsibilities and job description for the Senior Scientist, Real World Evidence Generation position at Tempus?
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.
We are looking for a Senior Scientist, Real-World Evidence Generation to join our Medical Science team at Tempus. This role will report into the Senior Director, Evidence Generation, and will be based at the Tempus hub in Chicago, IL; New York, NY; or Redwood City, CA.
Responsibilities:
- End-to-end execution of studies to demonstrate the clinical validity and clinical utility of Tempus products using Tempus real-world, multi-modal data
- Study design, data feasibility, and performing analyses using Tempus real-world, multi-modal data
- Working closely with the Clinical Development department and cross-functional teams including including Medical, Commercial Markets, Data Science, and Biostatistics to ensure studies meet evidence needs for reimbursement, clinical adoption, and biopharma
- Communication of study findings via presentations, abstracts, and peer-reviewed manuscripts; disseminating study findings across the company and externally through conferences and with biopharma and academic collaborators, regulatory agencies and reimbursement administrators, and clinical guideline bodies
- Stay current with industry trends, best practices, and advancements in molecular diagnostic evidence development and real-world data, and apply this knowledge to enhance studies
Qualifications:
- PhD (or equivalent experience) in Computational Biology, Molecular Biology, Health Economics, or related discipline
- Minimum of 2 years of industry experience in relevant areas:
- Experience in leading study design and execution in cross-functional teams
- Experience working with genomic (e.g., DNA-seq, RNA-seq), real-world clinical (survival data, EHR) and/or health claims data
- Computational skills, preferably with fluency in Python/R
- Strong peer-reviewed publication record
- Excellent written and verbal communication skills, with the ability to present complex information clearly to internal and external stakeholders
- Ability to work collaboratively in a team environment and lead cross-functional teams
- Strong analytical thinking, strategic thinking, implementation, and research skills
- Ability to multitask, prioritize, and navigate ambiguous situations
- Goal orientated, self-motivated, and driven to make a positive impact in healthcare
- Thrive in a fast-paced environment with the ability to adapt to changing priorities
Preferred Skills:
- Strong database and SQL skills (Redshift, BigQuery, dbt)
- Experience in Oncology
- Experience in Molecular Diagnostics
- Previous experience developing and submitting clinical evidence to regulatory agencies, reimbursement administrators, or clinical guideline bodies using real-world data
- Clinically-minded scientist, laser-focused on ensuring studies meet a clinical unmet need
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