Translational Scientist - Pre-Sales Solutions (Translational Research) - Location Flexible

Passionate about making a difference in the world of cancer genomics?

Tempus is a healthcare technology company at the forefront of the expansion of multi-modal healthcare data and the application of artificial intelligence (AI) to fundamentally change cancer care.  Tempus is growing, and we are seeking exciting new talent to join the team.

Tempus' proprietary platform connects an entire ecosystem of real-world data to deliver real-time, actionable insights enabling physicians to drive better outcomes through precise, individualized care.  Our data accelerates the pace of innovation, empowering researchers to characterize disease, discover new opportunities, maximize clinical trial success, and ensure new therapies reach the right patients. As a Tempus employee you will have access to the world’s largest real-world patient clinical data set linked to transcriptomics and digital pathology.

We are looking for a Pre-Sales Solutions Scientist to join our Translational Science team. This team collaborates with the world’s leading pharmaceutical organizations, utilizing Tempus’ data and platforms to deliver transformational impact across the entire drug development lifecycle. 

In this role, the successful candidate will work with Tempus’ business development and research teams to define strategic collaborations with industry partners. You will design research and analysis projects to advance drug target discovery, biomarker identification, clinical trial design, and commercialization, leveraging the Tempus ecosystem of NGS assays, real-world clinical and molecular data, modeling lab capabilities, smart trial matching, and AI. 

As such, the candidate will get a chance to work with one of the largest molecular and clinical databases of cancer patients in the world, work with leading drug companies developing the next generation of cancer therapies, and have a direct impact on patient care. This role is aimed to be 30% client facing. 

Responsibilities:

• Design clinical and molecular data analytics solutions for every step of the drug development pipeline in consultation with biotech and pharma scientific leaders
• Determine how Tempus assays can be used to for biomarker identification and patient enrollment
• Serve as the technical and scientific expert on client calls 
• Become an expert in Tempus multimodal clinical and genomic data
• Query the Tempus database to assess cohort feasibilities and create proof of concepts
• Work with business development teams develop proactive data packages to drive sales 
• Analyze and integrate large diverse clinical and molecular datasets to extract insights and drive new research opportunities across drug discovery portfolios
• Document, summarize and communicate highly technical results and methods clearly to non-technical audiences.

Required Qualifications:

• Education to Masters or PhD level combining quantitative and/or computational skills (Computational Biology, Biostatistics/Statistical Genetics, Bioinformatics, Cancer Biology, or similar)
• Highly proficient in R programming 
• Strong background in cancer biology
• Good data visualization skills and familiarity with R data visualization packages (ggplot2) and extending ggplot2
• Strong communication skills in a client-facing environment
• Thrive in a fast-paced environment and willing to shift priorities seamlessly
• 10% Travel

 Preferred Qualifications:

• Experience in SQL and establishing database connections within a R session.
• Familiarity with Python and the reticulate package
• Experience with engineering practices for research computing (Docker, Git and Github, code review, linux, cloud computing)
• Strong peer-reviewed publication record
• Experience working with real world evidence clinical cancer data (progression free vs overall survival, clinical trial design, data imputation and managing missing variable bias, etc)
• Understanding of CLIA/CAP validation protocols and how to bring scientific ideas to market
• Experience working with unstructured clinical and molecular data
• Familiarity with Bioconductor and working with S4 class