Lead, Risk Adj-Pred Analytics - Python Scripting/SQL/Databricks - Remote

$80,412 - $188,164/Yr

Molina Healthcare - Layton, UT

Full-time

Remote - Layton, UT

Insurance Carriers and Related Activities

About the position

The Lead, Risk Adjustment - Predictive Analytics role at Molina Healthcare is responsible for supporting the Risk Adjustment Predictive Analytics team by designing and developing systems for tracking and analyzing risk scores. This position involves providing training to team members, conducting data analysis, and collaborating with various stakeholders to ensure effective intervention strategies are implemented. The role requires a strong background in data analytics, SQL, and statistical methodologies to derive insights from complex datasets.

Responsibilities

• Assist Risk Adjustment Data Analytics Leaders in Prospective and Retrospective Intervention Strategy Analytics along with corresponding tracking of progress and impact of such interventions.
• Design and develop ad-hoc as well as automated analytical modules related to Risk Adjustment for Medicaid, Marketplace, and Medicare/MMP.
• Assist in designing and developing Automated Suspect and Target/Ranking Engine for all lines of business.
• Conduct analysis and reporting related to Managed care data like Medical Claims, Pharmacy, Lab, and related financial data like risk score, revenue, and cost.
• Perform root cause analysis for business data issues and report findings and resolutions to leadership.
• Design and lead development of tracking system for risk scores for all intervention outcomes and for overall markets and LOB.
• Work in an agile business environment to derive meaningful information from complex organizational data sets through data analysis, data mining, verification, scrubbing, and root cause analysis.
• Collaborate with interdepartmental and intradepartmental stakeholders along with Molina Executives to establish and deliver business requirements and data points.
• Analyze data sets and trends for anomalies, outliers, and opportunities using statistical tools and techniques.
• Assist with research, development, and completion of special projects as requested by various internal departments or external organizations.
• Act as a subject matter expert by following CMS/State regulations related to Risk Adjustment Analytics and provide necessary training.
• Track, facilitate, and manage changes in the Datawarehouse platform and perform upgrades to analytics reporting modules.
• Conduct preliminary and post-impact analyses for any logic and source code changes for data analytics and reporting modules.
• Develop training modules to help analysts understand processes and solutions.
• Maintain a team culture to adopt a fast-paced agile environment and foster a positive attitude towards challenging projects.
• Take accountability for tasks and projects assigned.

Requirements

• Bachelor's Degree in Computer Science, Finance, Math, Economics, or equivalent discipline.
• 6+ years of experience in data mapping, scrubbing, scrapping, and cleaning of data.
• 5+ years of experience in a Managed Care Organization executing a techno-functional role involving complex SQL Queries, Functions, Procedures, and Data design.
• 5+ years of experience with Microsoft T-SQL, SSIS, and SSRS.
• Familiarity with Data Science Techniques and languages like Python and R programming is an advantage.
• 5+ years of experience in analysis related to Risk Scores, Encounter Submissions, and Payment Models for at least one line of business among Medicaid, Marketplace, and Medicare/MMP.
• 5+ years of experience in Prospective/Retrospective/Audit targeting Analytics and Reporting.
• 5+ years of experience in working with complex data problems in quantifying, measuring, and analyzing financial/performance management and utilization metrics.
• 5+ years of experience in Statistical Analysis and forecasting of trends in medical costs.

Nice-to-haves

• Familiarity with Data Science Techniques and languages like Python and R programming.

Benefits

• Competitive benefits and compensation package.