Chief Analytics Architect for Payment Integrity

United States Digital Space LLC; United States; Remote; USD 98,000 - 164,000; Full time

Benefits offered by this job

Health benefits

401(k)

Life insurance

Tuition reimbursement

Paid time off

Paid holidays

Leaves of absence

Job summary

Cigna is seeking a highly skilled analytics and data science leader to advance AI-enabled analytics, automation, and enterprise data initiatives within Payment Integrity. You will drive model development, data strategy, and modernization to improve claim accuracy, reduce waste, and enhance operational efficiency.

The role requires deep proficiency in data science, predictive analytics, and data governance, with the ability to lead cross-functional teams and deliver measurable enterprise value.

Qualifications

• Advanced data mining and analytics experience with healthcare or similar domains.
• Experience in building predictive models and ML solutions for business impact.
• Strong data visualization and storytelling using BI tools like Power BI or Tableau.
• Ability to translate complex data into actionable business recommendations.

Responsibilities

• Lead analytics and data science initiatives to improve payment accuracy and operational efficiency.
• Develop AI-enabled analytics, automation, and modernization strategies.
• Collaborate with engineering, product, and business teams to scale data assets and solutions.
• Define data requirements, governance, and data quality improvements across initiatives.
• Evaluate AI/ML technologies and validate models with performance monitoring.

Skills

Data mining

Analytics

Machine learning

Statistical modeling

Data visualization

Education

Bachelor's degree

Tools

SAS

Altair

SQL

TOAD

Python

R

Job description

Cigna is seeking a highly skilled analytics and data science leader to advance AI-enabled analytics, automation, and enterprise data initiatives within Payment Integrity. You will drive model development, data strategy, and modernization to improve claim accuracy, reduce waste, and enhance operational efficiency.

The role requires deep proficiency in data science, predictive analytics, and data governance, with the ability to lead cross-functional teams and deliver measurable enterprise value.