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 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 characterizing 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-reviewed 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.