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Director, Advanced Analytics

2 months ago


Chicago, United States Elevance Health Full time

Location: This position will work a hybrid model (remote and office). The ideal candidate will live within 50 miles of one of our Elevance Health PulsePoint locations.

The Director, Advanced Analytics will be responsible for planning, directing, and controlling the resources and efforts of an advanced analytics team to accomplish the company objectives through program evaluation, analyses, and general analytic consulting to Elevance Health stakeholders and partners.

How you will make an impact:

  1. Manage day-to-day research activities of a team of advanced analysts in a particular subject matter domain (e.g., Value-Based Care, Care and Disease Management, Vendor Solutions, Utilization Management, Performance Guarantees, etc.) or specific functional area (such as data extraction and management).
  2. Ensure enterprise accountability of the organization’s data and AI assets to drive value for business stakeholders.
  3. Establish, lead, and operate the data engineering and artificial intelligence function to deliver agile solutions while managing data as a valued asset.
  4. Support program teams by providing continual feedback on program performance, identifying drivers of success, and insights into future opportunities for program enhancements or expansions.
  5. Hire, train, coach, counsel, and evaluate performance of direct reports.

Minimum Qualifications:

Requires a BA/BS in Health Services Research, Health Economics, Epidemiology, Statistics, Applied Mathematics, or a related research-oriented discipline and a minimum of 10 years’ experience leading evaluation/research/consulting projects and teams; or any combination of education and experience, which would provide an equivalent background.

Preferred Skills, Capabilities, and Experiences:

  1. Knowledge of statistical software and analytic platforms strongly preferred.
  2. Advanced degree in a research-oriented discipline (Health Services Research, Health Economics, Epidemiology, Statistics, Applied Mathematics, etc.) and prior leadership/management experience preferred.
  3. Expertise with cutting-edge technologies such as transfer learning, unsupervised feature generation, meta-learning, generative text models, computer vision, sensor fusion, or reinforcement learning.
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