Senior Scientist, Life Science and Research Analytics

Key Skills

Aartificial intelligence, AWS, CSS3, Data science techniques, Docker, Effective communication skills, Flask, NumPy, Pandas, Python Programming, R Programming, SciPy, SQL

Job Description

The Senior Scientist, Life Science, and Research Analytics in the Real World Data Science org will leverage Tempus' multimodal database to deliver proof of concept studies and actionable findings with a strong commercial focus to internal and external stakeholders. This role will deploy a consultative approach to understand where insights from Tempus’ database can meaningfully impact patient care or development programs. In this team, you will design and perform complex computational analyses, pitch presentations, and publications to guide decision-making for biopharma and medical providers. These initiatives will deliver transformational impact in the clinical setting and across the entire drug development lifecycle. Top candidates will possess strong cancer biology and genomic analytical training and the ability to communicate complex scientific findings to diverse audiences.

Key Responsibilities:

Independent Contribution:

• Independently execute complex translational and real-world evidence research projects integrating molecular and clinical data from the Tempus multimodal platform to derive novel insights.

Leadership:

• Manage scientific activities, including scoping net new projects, generating high-quality contracted deliverables, and serving as the key scientific lead.
• Coordinate with leads in Research, Engineering, Data Science, and Medical Affairs to identify and develop value-creation opportunities.
• Help train and manage junior scientists on the team.

Scientific Communication:

• Present scientific findings clearly and meaningfully to diverse sets of internal and external stakeholders.
• Document, summarize, and communicate highly technical results and methods clearly to non-technical audiences.
• Author whitepapers and peer-reviewed publications to illustrate the value of multimodal analysis and AI in drug discovery.

Continuous Improvement:

• Stay current with industry trends, best practices, and advancements in computational oncology research to identify specific areas where the Tempus platform can establish new markets.
• Conduct pipeline and portfolio reviews to proactively determine all areas where the Tempus platform could add value to the drug development or clinical setting.
• Apply this knowledge to enhance research methodologies and improve overall research and Tempus offerings.
• Partner with our pharma clients and commercial teams to co-architect computational research projects leveraging the Tempus platform to advance precision medicine research programs.
• Develop and drive global account strategy in coordination with commercial and medical teams.

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 in 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
• 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.