bcbsnc
Principal Data Scientist
At a Glance
- Location
- Flex, North Carolina, United States
- Employment
- Full time
- Experience
- 8+ years
- Compensation
- t and individual performance. $143,616.00 - $229,786.00
- Posted
- 2026-08-06
Key Requirements
Required Skills
Domain Knowledge
- Engineering
- Finance
- Healthcare
- Medical
- Mining
Requirements
Experience building AI Agents
Understand Bell curve analysis
Incorporate Industry benchmarks into analysis
Perform outlier detection
Strong healthcare experience with Payment Integrity/FWA business knowledge is required
understanding of FWA concepts, CMS guidelines, Medical/Reimbursement Policy are all strongly preferred
Compensation & Benefits
At Blue Cross NC, we take great pride in a fair and equitable compensation package that reflects market-price and our starting salaries are typically planned near the middle of the range listed. Compensation decisions are driven by factors including experience and training, specialized skill sets, licensure and certifications and other business and organizational needs. Our base salary is part of a robust Total Rewards package that includes an Annual Incentive Bonus*, 401(k) with employer match, Paid Time Off (PTO), and competitive health benefits and wellness programs.
*Based on annual corporate goal achievement and individual performance.
$143,616.00 - $229,786.00
Responsibilities
The Principal Data Scientist will serve as the principal lead to provide accurate and quality analyses that translate data in sound organizational decisions.
In this role you will provide strategic thought leadership and partner with other functional areas to deliver collaborative work products that align with divisional and enterprise strategy.
You will own delivery of multiple large and/or complex data science and engineering projects.
Lead in the development and testing of hypotheses across all functional data sets
Lead requirements gathering sessions with business and technical staff to distill technical requirement from business requests
Define and implement integrated data models, allowing integration of data from multiple sources