Data Scientist

MedPro   •  

Fort Wayne, IN

Industry: Accounting, Finance & Insurance

  •  

5 - 7 years

Posted 77 days ago

This job is no longer available.

Data Scientist

We are seeking experienced members to join the MedPro Group who are passionate about data and applying the latest machine learning technology to solve business problems. As part of a newly developed Data Science team, you will lend your hand in designing, and building out, the tools to help progress the company along its digital journey. In this role, you will utilize a vast amount of data to help develop a deep understanding of underwritingrisk, reduce the volatility of medical malpractice claims, and build common analytic platforms across our diverse businesses. You will also build deep learning models for medical data extraction, mobile app deployment for production models, and an assortment of dashboards to drive actionable decisions.

You will have an impact on patient safety and the quality of billions of procedures performed annually by the 200,000+ MedPro Group insured healthcare providers. This position reports to the Lead Data Scientist and is an opportunity to get in on the ground floor of a quickly growing team with high visibility.

What We Look For:

  • We have a large number of projects in underwriting, claims, marketing, security, and online areas, which gives team members a lot more freedom of direction. As a result, we find that driven and genuinely curious people thrive here (not what but why).
  • You would be involved with multiple projects, with timelines from days to months. We look for the ability to use independent judgment and initiative, and to anticipate the needs of leadership. We desire candidates who can accomplish tasks without extensive direction. This will mean top-notch experience leading a diverse set of small projects with limited oversight.
  • Our colleagues have diverse backgrounds; as such, candidates must be comfortable in an environment of whiteboard sessions to bounce ideas around on experiment design and approach, both on-site and remotely.
  • Part of developing a first-rate data science team is improving the overall knowledge base of the company. Your projects and case studies will be used to teach areas of the business new analytical tools, techniques, and visualizations, and to reinforce the idea that data is our strongest asset. Published work / prior teaching experience is a plus.
  • Our team functions as an internal consultancy; you will need to develop strong working relationships between many different departments. As such, we look for the ability to positively represent your Data Science team, interact and provide direction to members at all levels and departments at MedPro, and be able to speak to what is new and upcoming in our field.

What skills you need:

Infrastructure and Design:

  • Familiarity with data warehousing solutions and associated pipelines for internal/external sources, including ETL tools.
  • A strong history of good experiment design and related project management skills. Your documentation will often be the basis for outside departmental training.

Data Munging:

  • Strong experience with data munging in SQL and NoSQL environments for both structured and unstructured data.
  • Experience sourcing and merging additional external sources of data.

Model Development and Deployment:

  • A strong history working throughout the complete lifecycle (from idea to execution) for machine learning in Python or R. This would include parametric and non-parametric modeling for supervised and unsupervised solutions.
  • A strong understanding in the different ML techniques and variable reduction approaches as well as parameter and hyper-parameter tuning.
  • Visualization experience in dashboards (Tableau) and web apps (R Shiny).

Education/Experience:

  • Masters in statistics or related field, PhDs or a record of accomplishment of continued learning is preferred.
  • 4+ years of technical experience with the above qualifications.
  • Experience with medical malpractice, workers compensation, or other low-frequency, high-severity industries is preferred, but not required. Experience with dirty medical data also preferred.