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Data Operations Analyst

Passionate about making a difference in the world of cancer genomics?

We now have more data than ever before but providers don't have the infrastructure or expertise to make sense of said data. Here at Tempus, we are building the infrastructure to modernize cancer treatment and derive insights from the mass accumulation of clinical and molecular data. There is an endless stream of questions that we can ask of the data- and we need your help to find the answers!

What You'll Do:

  • Work with our external data partnership and business development teams to build a full picture of existing and new data attributes
  • Profile and analyze data to identify opportunities to both improve and to put to use segments of the Tempus data asset
  • Work closely with other Tempus teams in identifying ways to use Tempus data assets to drive patient outcomes and growth opportunities at Tempus
  • Team up with other Tempus analysts to quickly respond to query requests from internal and external key stakeholders
  • Own quality control of inbound and outbound datasets
  • Work with internal teams to identify and resolve risks to data quality and integrity
  • Become an expert in our data infrastructure and serve as an internal resource as other teams integrate with new data stores


  • Bachelor's degree in analytics, business, computer science, finance or economics
  • 2+ years of experience with SQL, Excel, and Tableau
  • Practical experience translating raw data into practical insights and recommendations
  • Prior experience with visualizing data (e.g. Tableau, Plotly, R, Power BI, or other graphical tools/packages)
  • Excellent project management skills, with proven ability to execute highly complex projects with multiple cross-functional stakeholders
  • Ability to effectively prioritize in a dynamic, and time sensitive environment with minimal guidance
  • Experience working with disorganized data

Nice to Haves:

  • Experience working with clinical and/or genomic data
  • 2+ years of consulting, investment banking, project management or operations
  • Experience working with data in Python (e.g. Pandas, Numpy, etc)
  • Experience presenting results of analysis to an audience of various levels of data/technical competency
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