Scientist II, Real World Data Science - Translational Research

With the advent of genomic sequencing, we can finally decode and process our genetic makeup; however, computer technology has had limited impact in healthcare. With the expansion of multi-modal healthcare data and recent advancements in AI, that’s about to fundamentally change. Tempus is a healthcare technology company at the forefront of that change to leverage data to improve patient lives.

Tempus' proprietary platform connects an entire ecosystem of real-world data to deliver real-time, actionable insights to physicians. Our data empowers researchers to better characterize and understand disease, and to drive better outcomes through precise, individualized care.

The Senior Scientist, Translational Research or Real-World Evidence in the Real World Data science org  will design and execute research projects for early stage to mid stage biopharmaceutical partners. This role involves performing complex computational analyses, and providing interpreted  insights in a consultative approach  to guide decision-making for biopharma clients.  This role will require staying up to date in research and industry trends in oncology drug development to identify specific areas where the Tempus platform can establish new markets.

Key Responsibilities:

• Execute  Strategic Collaborations: 
• Partner with our pharma clients to design, develop and execute computational research projects leveraging the Tempus platform to advance precision medicine research programs.
• Execute scientific activities including scoping net new projects, generating high quality contracted deliverables and serve as the key scientific lead in the partnership.
• Support exploratory research for target discovery and validation  in early phases of drug development.
• Support decisions for early stage assets such as patient and indication selection, biomarker and combination strategies.
• Evaluate clinical trial design by testing assumptions, refining eligibility criteria, and characterize patient outcomes on standard of care.
• Develop novel biomarkers of response signatures.  
• Leadership Development:
•  Help train and manage  junior scientists on team
• Independent Contribution:
• Independently execute complex translational or real-world evidence research projects integrating molecular and clinical data from Tempus multimodal data platform to derive real-world insights for biopharma partners.
• Scientific Communication: 
• Expert in navigating client interactions; Present scientific findings clearly and meaningfully to diverse sets of external stakeholders.
• Document, summarize and communicate highly technical results and methods clearly to non-technical audiences.
• Author abstracts, posters and peer-review publications to  illustrate the value of multimodal analysis and AI in drug discovery in coordination with our partners or internal R&D teams.
• Continuous Improvement: 
• Become an expert in our biopharma partners’ strategy, pipeline and portfolio to proactively determine all areas that the Tempus platform could add value to the drug development process of our partners.
• Stay current with industry trends, best practices, and advancements in computational oncology research. Apply this knowledge to enhance research methodologies and improve overall research quality on the team.
• Work with Product and Engineering teams to streamline workflow of computational analyses.

Qualifications:

• Education: PhD degree in a quantitative discipline (e.g. Biostatistics/Statistical Genetics, Cancer Genetics, Bioinformatics, Computational Biology, Computational Immunology or similar) plus 2 years of experience or postdoctoral studies. Alternatively, a PhD in Molecular Biology or Immunology combined with a very strong record of computational biology.
• Experience: Minimum 2 years in drug development leveraging genomic and multimodal data for drug discovery and development .
• Technical/Scientific Skills: Proficient in R, Python, and SQL. Strong understanding of cancer biology
• Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences. 

Preferred Skillsets/Background:

• Strong understanding of molecular data and artificial intelligence in drug discovery with experience in integrative modeling of multi-modal clinical and omics data.
• Previous experience working with large transcriptome and NGS data sets.
• Prior consulting and/or client facing experience is highly desirable
• Ability to work collaboratively in a team environment
• Thrive in a fast-paced environment and willing to shift priorities seamlessly.
• Experience with R package development.
• Strong peer-reviewed publication record.
• Experience with: Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, R Package development,  tidyverse, ggplot, Git, matplotlib, seaborn, HTML5, CSS3, JavaScript, D3, Plot.ly, Flask, Dask, Docker, AWS.
• Goal orientation, self motivation, and drive to make a positive impact in healthcare.