Director, Research Data

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.

We are seeking an experienced scientist with a strong background in engineering to lead the development of Tempus' multi-modal molecular data model. This scientist will be responsible for managing cross-functional projects across science and engineering to build scalable systems that enable clear standardization, versioning, harmonization, and documentation across the data production life cycle. This role will be at the forefront of developing and applying computational methods and engineering best practices to Tempus' large clinico-genomic data model while working closely with engineers, product managers, researchers, and clinicians. This role demands a blend of creative and strategic thinking, leadership skills, and a passion for groundbreaking research. 

The ideal candidate will be an expert in computational biology and multi-dimensional data modeling, with a track record in (or with) biopharma drug development and designing large-scale data models. The candidate must be experienced in NGS workflows, harmonizing public data sources, and have experience managing work at the intersection of research and engineering. 

This position is a scientist role with a strong integration into engineering workflows. Contributions to data analysis and interpretation as well as creating engineering specifications are expected while also managing work across a cross-functional team of scientists and engineers.

Key Responsibilities:

• Scientific:
  • Develop and implement scientific strategies for the production and usage of data across different scientific domains including bioinformatics, computational biology, cell-imaging, and cell-modeling 
  • Design multi-modal and dimensional data models which address a wide range of user needs, including Tempus-researchers and biopharma partners
  • Create user documentation and best practices on data model usage for researchers, publications, algorithm development, and clinical workflow
• Engineering:
  • Work closely across engineering teams to define and implement systems to enable the automation of data creation, documentation, versioning, and quality control
  • Define engineering specifications for the creation of tables in the Tempus Data Model
• Managerial:
  • Manage a Jira board tracking cross-functional data product life cycle from inception to client delivery
  • Manage a team of scientists who work across the data life cycle 

COLLABORATION: 

• Communicate the scientific and technical plans and outcomes to a cross-functional group of project and senior leadership stakeholders, both internal and at biopharma partners
• Work closely with other cross-functional teams across Tempus (product, engineering, operations, clinical genomics labs, medical, science, data science, etc) to integrate work plans to achieve end-to-end molecular data needs. 
• Foster a collaborative and inclusive work environment, promoting interchange of expertise between Tempus and biopharma partner contributors, and driving creativity, innovation, and scientific excellence.

Preferred Qualifications:

• PhD with 6+ years of work experience
• Education and experience must combine:
• Quantitative and computational skills (e.g. Computational Biology, Biostatistics/Statistical Genetics, Bioinformatics, Biomedical Informatics, Biometrics, or Data Science for Health)
• Biological or medical knowledge (e.g. Human Disease, Oncology, Genetics/Genomics, Molecular Biology, or Immunology)
• Engineering best practices and model design in SQL databases
• Multidisciplinary project team leadership experience
• Proficient in SQL and R or Python packages for computational biology
• Ability to deliver actionable insights from NGS, clinical, and/or real-world data sets
• Competency in statistical and mathematical techniques for biological data analysis

#LI-GL1