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Lead Data Scientist


Job Title

Lead Data Scientist - Healthcare

Full-Time, Salaried, Chicago, IL

Job Description

The Lead Data Scientist will be responsible for leading Fibroblast’s initiatives in the areas of advanced analytics, business intelligence, algorithm development and optimization, and machine learning. This position reports to the VP of Product. While this position may require some travel (1-2 days / month), the candidate must live in the Chicago area.

You are responsible for

  • Development of advanced analytic methodologies applied to application data, healthcare claims data, and other integrated data sources in service of our analytic products and services:
  • Advanced data mining and normalization of large healthcare claims data sets across multiple sources and formats
  • Provide technical design and implementation of data models and data sources to further our product offering in the areas of machine learning and algorithm
  • Routine and ad-hoc reporting on customer dashboards, business insights, and performance reports
  • Leadership in the area of operational analysis which generates actionable improvements on our processes and products
  • Continued development of our data visualization/presentation methodology and delivery
  • Contribute to the continued improvement of internal data modeling and warehousing technical infrastructure
  • Identify and oversee the integration and maintenance of external data sources into our existing product and service offerings
  • Work with Fibroblast business units and product teams to identify additional advanced analytic needs
  • Communicate complex analytics methodology in a clear and concise manner to non- technical stakeholders and customers
  • Manage the permissions and distribution of analytic product suite in a HIPAA compliant manner
  • Collaborate with contractors and/or vendor resources on data projects as needed

To succeed in this role, you should have the following skills and experience

  • Bachelor’s or Master’s degree in Math, Statistics, Computer Science, Artificial Intelligence or other related field
  • 5+ years experience with applying advanced statistical, machine learning, and/or data mining techniques to real-world problems using large healthcare claims data sets or similar data
  • Experience in the healthcare industry or work with health care data such as claims, EMR, etc.
  • Strong experience using analytic tools such as  SQL,  PYTHON, SAS, R, EDM, etc.
  • Strong experience with BI data visualization tools such as Tableau, Qlik, Domo, Highcharts, etc.
  • Experience with customers and conducting presentations
  • Strong written and verbal communication skills

What we’re offering

  • Competitive salary
  • Stock options in a growth-stage company
  • Medical, dental, and vision insurance
  • Life insurance, disability benefits, and 401k Retirement
  • Unlimited vacation
  • High-energy work environments at our office in MATTER, a community of over 200 healthcare focused companies
  • Membership at MATTER, providing:
  • Participation in a strong community of start-up entrepreneurs and engineers
  • Free access to MATTER networking and educational events
  • Opportunities to access and build relationships with MATTER mentors and industry and investor partners
  • The latest equipment including Macbooks and large monitors
  • Weekly sponsored team happy hours
  • Tons of snacks and catered lunch weekly
  • Discounts on tons of useful services (Zipcar, etc.)

About Fibroblast
Fibroblast automates the referral and population health management processes by empowering providers and their administrative staff with an easy to use, end-to-end referral management platform.  Our secure, HIPAA-compliant platform enables office staff to source referrals and schedule provider appointments at the point of care. Fibroblast can be used as either as a stand-alone solution, or tightly integrated with existing EMR, PM, eMPI, analytics, or disease registry systems as desired. Fibroblast’s proprietary, intelligent patient-provider matching algorithm takes into account a variety of variables to drive referrals to the most appropriate in-network providers delivering the highest quality, lowest cost care.

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