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

We now have more healthcare data than ever before, but providers often do not have the systems or expertise to make sense of all of this valuable data. At Tempus, we are building the infrastructure to modernize and enhance cancer treatment. We are on a mission to connect an entire ecosystem to redefine how data is used to improve patient outcomes. The Clinical Informatics team is seeking a solutions-oriented engineer who enjoys innovation, process improvement, and working with complex datasets. 

What you’ll do:

As part of the informatics team, you’ll play a key role in helping us aggregate data from many different sources to build the largest library of oncology clinical data in the world.  You’ll work with clinical data experts, engineers, data scientists, and informatics analysts to process and standardize data for use in a variety of applications.

Responsibilities:

  • Lead efforts to build an extensive toolkit for normalization and mapping of disjoint data
  • Build and maintain a database of medical terms and codes and process text to extract concepts, relationships, and knowledge
  • Automate quality assurance to ensure that data adheres to a common set of standards
  • Identify and socialize improvements to data processing infrastructure and workflow
  • Analyze the quality of our data and insights that can be generated from it
  • Establish, monitor and optimize infrastructure and application-level stability, performance and reliability measures and metrics
  • Plan team testing activities and support scheduled releases and deployments

Skills and Qualifications:

  • Bachelor degree in Computer Science, Information Engineering, Information Systems, or a related discipline; Master’s degree preferred
  • Advanced skills in Python & SQL; experience with Javascript
  • Experience automating workflows using Airflow
  • Prior work experience in the AWS ecosystem
  • Experience working with ETL development + processing and cleaning disorganized data from various sources

Nice-to-haves:

  • Familiarity with Oncology and Cancer Genomics
  • Knowledge of Biomedical and/or Clinical Informatics
  • Experience with NLP techniques

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