Risk Adjustment Predictive Analytics Analyst

Molina Healthcare; Arizona; On-site; USD 49,000 - 107,000; Full time

Job summary

Molina Healthcare is seeking an analyst to support enterprise risk adjustment predictive analytics. The role designs and develops suspect, targeting, and tracking systems to support Molina’s prospective and retrospective interventions.

The position involves QA reporting, automated analytics modules, and working in an agile environment to derive insights from complex health-care data, with effective communication to non-technical stakeholders.

Qualifications

• 2+ years of experience writing complex SQL queries and working with relational databases (T-SQL, SSIS, SSRS, Power BI).
• Analytical mindset with attention to detail and problem-solving skills.
• Experience handling complex health care data, cost and utilization metrics, and predictive modeling.
• Experience with Microsoft Azure, AWS, or Hadoop.
• Ability to manage multiple priorities in a fast-paced environment.

Responsibilities

• Assists analytics leaders in prospective and retrospective intervention analytics and tracking progress.
• Develops QA ad-hoc and automated reporting for Medicaid, Marketplace, and MMP lines.
• Assists in developing automated suspect and target/ranking engines across lines of business.
• Facilitates analysis of managed care data (claims, pharmacy, lab, financial data).
• Calculates and tracks risk scores for intervention outcomes across markets.
• Performs data analysis, mining, verification, scrubbing and root-cause analysis in an agile setting.
• Conducts root-cause analysis for business data issues.
• Supports special projects for internal departments or external agencies.

Job description

Molina Healthcare is seeking an analyst to support enterprise risk adjustment predictive analytics. The role designs and develops suspect, targeting, and tracking systems to support Molina’s prospective and retrospective interventions.

The position involves QA reporting, automated analytics modules, and working in an agile environment to derive insights from complex health-care data, with effective communication to non-technical stakeholders.