Associate Principal Data Scientist, FUSES & Pharma R&D

Passionate about precision medicine and advancing the healthcare industry with AI?

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 and pharma, providing critical information about the right treatments for the right patients, at the right time.

The Associate Principal Data Scientist will apply Computational Biology, Machine Learning & Generative AI to build an LLM driven discovery platform and resulting library of predictive models for established oncology therapies. This role involves performing complex computational analyses and developing algorithms for advancing cancer precision medicine for patients across the Tempus network. The ideal candidate will possess strong applied machine learning and generative AI skills, experience in applying various models to big data, and the ability to communicate complex findings to various stakeholders.

Description

• Data Expertise: Tempus has one of the largest multimodal patient datasets ever collected, providing a unique opportunity to work with extensive and diverse data. Become an expert in Tempus’ vast epidemiological, clinical, ‘omic and imaging data, along with the latest tools and techniques for their analysis and modeling. 
• Innovation: build an LLM driven discovery platform leveraging Tempus’ vast real world database to discover predictive opportunities guiding optimal therapy, fusing features from multiple data modalities, and establish a library of biomarkers and predictive model prototypes for established oncology therapies.
• Leadership: mentor, strategically lead, and manage delivery from a cross-functional project team.
• Teamwork and collaboration: Work with Research, Engineering, Data Science and Product teams across Tempus’ expansive data science community.
• Clinical and Drug R&D Expertise: Work with leading professionals in the medical and pharmaceutical industries. Gain proficiency in their strategies, drug modalities, and pipelines to identify where the Tempus platform can add value.
• Scientific Communication: Skillfully communicate complex technical results and methodologies to diverse internal and external stakeholders; published in peer reviewed journals.
• Personal development: Continuously immerse yourself in the latest industry trends, best practices, and advancements in machine learning and AI to revolutionize clinical care and drug R&D

Qualifications

• Education and experience:
• Either
• PhD and an additional 4+ years of working experience
• Masters and additional 6+ years of working experience
• Combining:
• Quantitative and computational skills (e.g. Applied Machine Learning, Generative AI, Large Language Models, Computational Biology).
• Biological or medical knowledge (e.g. oncology, immunology, genomics, transcriptomics).
• Biomarker, target, drug or diagnostic discovery, or clinical drug development.
• Technical/Scientific Skills:
• Proficient in R, Python, and SQL, and respective packages for computational biology and machine learning.
• Applicable knowledge of machine learning, particularly large language models, and statistical modeling.
• Strong understanding of the uses of artificial intelligence in molecular data analysis for predictive modeling or drug discovery/development.
• Experience in integrative modeling of multi-modal clinical and omics data.
• Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences. Comfort in a client-facing role.
• Motivated: Thrive in a fast-paced environment and willing to shift priorities seamlessly.

Preferred Skillsets/Background

• • Strong peer-reviewed publication record.
  • Strong understanding of cancer biology.
  • Expertise in biomedical data and precision medicine.
  • 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 real-world data, large transcriptome or NGS data sets.
  • Thrive in a fast-paced environment and willing to shift priorities seamlessly.
  • Experience with software development.
  • Goal orientation, self-motivation, and drive to make a positive impact in healthcare.

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