Engineering Manager, Data Science

Engineering Manager, Data Science

This job is no longer open

What’s weird about working with us?

  • We care, a lot. Our CEO spends substantial time regularly doing customer service, and many of our healthcare professionals and healthcare facility clients have her personal cell phone number. 
  • We are globally distributed. Just on the engineering team we have folks from: the United States, Chile, Mongolia, Turkey, India, Ukraine, Indonesia, Brazil, Columbia… and that’s just from folks who’ve joined us so far this year. 
  • We take our values seriously: our COO literally has a handmade Curiosity Initiative and Ownership sign on his wall (you’ll see it if you videocall him). 
  • We have more engineers than we “need” on purpose. It makes us fast (many features go from idea to production in 2-4 weeks). It also allows small teams to see a problem, and just go fix it. A team went off and created a new SaaS product, another team rewrote a core service under a new architecture. 
  • One thing we value is that we have no “toes” here to be stepped on. See a problem? Go ahead and fix it, you don’t need permission.

You're good at:

  • Leading and growing a team of ML Engineers, Data Engineers, and Data Scientists
  • Managing your teams’ performance to increase the output of the people you lead and others around them
  • Working with stakeholders in Product, Marketing, and Sales to design and validate ML powered experiments
  • Writing code as a part of your team to build scalable/high-performance ML powered applications, and understanding complex technical areas along the way
  • Guiding and making architectural decisions to build Clipboard Health's Data Science Platform, continuously improving MLOps and our ability to take ML powered applications from concept to production
  • Designing observability into ML powered applications to evaluate model quality and performance over time, detect feature drift, etc.

Extra Awesome if you are:

  • A fan of the speed of startups, having worked at one or more (including maybe your own) before
  • Familiar with modern ML and data tools like: PyTorch, TensorFlow, Python, pandas, OpenCV, scikit-learn, Kedro, MLFlow
  • Experienced in developing, monitoring, and maintaining ML powered applications on AWS, Amazon SageMaker, Elastic Inference, Snowflake, Fivetran, DBT

Perks of Working with us: 

  • Do great work that matters, in healthcare, for customers who could really use your help
  • Zero commute. Work wherever you are, globally (but on or around US Pacific Time hours)


This job is no longer open
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