With the advent of genomic sequencing, we can finally measure and process our genetic makeup. We now have more data than ever before, but providers often don't have the infrastructure or expertise required to easily extract the valuable insights that exist within this data. Here at Tempus we believe the greatest promise for the detection and treatment of cancer & other diseases lies in building a deep understanding of the interaction between molecular attributes and clinical treatment.
We're on a mission to redefine how genomic data is used in a clinical setting. We are looking for applied machine learning engineers who are passionate about the prospect of building the most advanced data platform in precision medicine.
What You'll Do
* Work with our data science teams to build data visualization and analysis dashboards and tools * Coordinate with science, data engineering, and devops teams to bring together the numerous sources of data required by the data science models * Become proficient in our data and engineering infrastructure components, and champion their continued improvement
Nice to Haves
* Experience building and validating predictive models on structured or unstructured data * Experience working with clinical and/or genomic data * Experience in agile environments and comfort with quick iterations * Experience with AWS architecture * Experience in High-scale web applications and architecture * Experience with continuous integration infrastructure for software development such as Jenkins * Experience with Docker
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