Statistical Analysis Data Reconfiguration Jobs in Kentucky

Job Description

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.

What You'll Do

• 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

• Design and develop scalable, efficient data pipeline processes to handle data ingestion, cleansing, transformation, integration, and validation

• Define and implement data stores based on system requirements and consumer requirements

• Design and develop models to understand and solve multiple complex business solutions using a variety of methods including data mining, statistical analysis, predictive modeling and analysis, stochastic modeling, pattern recognition, probability analysis, and network analysis

• Design and implement production models leveraging technologies such Python, and R

• Leverage existing data sets and engineer new data sets including development of SQL queries, data integration and resolution of data quality issues

• Apply advanced conceptual understanding of Big Data systems to data set engineering and analytic model implementation

• Lead development and reviews of complex analytic models and algorithms

• Identify actionable insights, suggest recommendations, and influence business direction by effectively communicating results to cross functional groups

• Document and test analytic processes including performance and thorough data validation and verification

• Engage with enterprise business areas to incorporate feedback into audit process including but not limited to Payment Integrity, SIU, Provider, Behavioral Health, Med Policy, Claims, Pharmacy
• Articulate analytic methods and drive business outcomes with responsible business areas
• Consult with executive level leadership across the organization- with responsibility to drive CoC ideation for Commercial and Medicare
• Informally lead other analysts and synthesize information and make recommendations to executive leadership

• Bachelor's degree or advanced degree (where required)

• 8+ years of experience in related field.

• In lieu of degree, 10+ years of experience in related field.

• Strong Analytic/Data Science skills:

• Experience with Snowflake

• 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

Salary Range

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

Skills

Big Data, Complex Data Analysis, Data Analysis, Data Engineering, Data Mining, Data Modeling Techniques, Data Science, Data Visualization, Machine Learning (ML), Predictive Analytics, Predictive Modeling, Python (Programming Language), Statistical Analysis, Statistical Models

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