Help build technology that saves lives!
LeanTaaS is a fast growing healthcare predictive analytics company that uses sophisticated math and lean principles to make healthcare providers more efficient.
Our technology helps millions of people wait less at hospitals and specialty clinics across the country.
Our customers include some of the nation's largest hospitals including Stanford, UCSF, NewYork-Presbyterian, the University of Texas MD Anderson Cancer Center, and more
Our team includes veteran executives and the brightest minds from Google, McKinsey, Stanford, MIT, Duke, Berkeley, UIUC, and more.
We are a Series B company backed by multiple prominent investors in the healthcare space.
You will work in a small data ingestion team that will focus on:
Understanding EHR data models and develop and refine EHR queries to fetch the data we need. We work with several EHRs such as EPIC, Cerner, Meditech, McKesson Paragon, etc. This requires research and intuition - you'll have to navigate your way through complex models.
Working with data teams at customer sites to ensure that the data is complete, accurate, and aligned with the structure we expect to see for the product. This requires a lot of data reverse engineering - you'll have to figure out what data should look like and what may have gone wrong and get to the bottom of it. This is perhaps the most fascinating part of this job.
Working with engineering and infrastructure teams to make our predictive models work at scale. This requires refactoring sophisticated algorithms and leveraging tools like Hadoop and Spark to improve efficiency and performance.
B.S. or M.S. (preferred) with major in Statistics and/or Computer Science.
1-2 years professional experience as a data engineer. No experience is also OK if you can demonstrate exceptional skills/abilities.
Strong R or Python skills and data analysis skills - many times, you will need to reverse-engineer the data: there's typically not good documentation available for the EHR data models you will work with, however, you'll need to find out what each column means and how to read different dimensions and values.
Strong data analytics skills - you should love to work with data and solve challenging data problems patiently.
Good communication skills - you will work directly with customers and therefore need to communicate well.
Nice to Have:
Experience with data analysis tools such as Tableau.
Experience with python data frameworks such as numpy, etc.
Experience working with EHRs.
Experience working on ETL.