Like many data scientists, I hear from recruiters nearly every week about exciting roles at really great companies. Why do I continue to choose Machinify?

‍The ability to have impact at Machinify is unparalleled. Our team is building machine learning solutions to tackle some of the biggest problems in healthcare. It is conservatively estimated that $350 billion of US medical spending is wasteful — not improving the health of patients. We have deployed a collection of models to detect that waste and directly reduce costs. Everyone, including patients, providers, and payers, stands to gain from that.

Our customers include the biggest healthcare organizations in the country, and they see enormous value from what we do. Just one of our models reduces $14 million of medical waste every year. How do we do that?

A diagram of Machinify's data process.

We build generalized models to classify medical claims and send predictions to administrative systems and teams to reimburse those claims correctly. We employ the best software and services available to:

  • process structured and unstructured data for millions of claims every day
  • design features and models general enough to classify every medical claim, yet flexible enough to adapt to specific healthcare policies
  • train, test, and score of hundreds of models automatically
  • receive daily feedback to continuously improve our models

This is truly machine learning deployed at scale! I am genuinely excited to work on these technical problems every single day. 

Data science is core to what Machinify does, so being data-driven is a given. We precisely measure outcomes, move on quickly from dead end projects, and continuously make forward progress. Our solutions are poised to become the best technology in the industry. 

This is only possible with a strong team, including leaders with a clear vision, industry veterans who understand our customers, and wicked-smart engineers and data scientists. Put simply, Machinify is serious about hiring and retaining top talent. 

If you would thrive in this kind of environment, then I want to work with you!

Check out our open roles and apply directly.

Liz Xiao
Liz is the Data Science Manager at Machinify and comes from a cool geographical location. This is something interesting about the author. Here's a personal blurb or quote. Here's a little bit about her career path and background. You can find here, doing something really cool, in her off time with the people she enjoys hanging out with. Contact her at here email, here or click this social media link here.