California Physicians' Service - Oakland, CA

posted 4 months ago

Full-time - Mid Level
Oakland, CA
Insurance Carriers and Related Activities

About the position

The Large Group Pricing team is responsible for setting accurate rates and forecasting future performance for fully insured employer groups. The Actuarial Analyst, Senior will report to the Director or Manager of Large Group Pricing. In this role, you will be responsible for developing our rating factors, including continually monitoring and improving the accuracy of our projections. You will be the main point of contact for our underwriting stakeholders, providing hands-on support and guidance with quoting. This role will also be responsible for reviewing and filing all required regulatory data in a timely manner. In this role, you will understand the core principles and functionality of decision, descriptive, and predictive analytic methods including forecasting, statistical, and machine learning techniques. You will conduct and develop analysis, assess risk and population risk scores and assignment, develop pricing and trends, assess changes in benefit designs, develop reserves, perform forecasting, analyze provider reimbursement terms, and evaluate actuarial risk related analysis. You will coordinate, prepare, perform, and audit actuarial analyses to assist in the development of complex actuarial formulations leading to the recommendation of pricing, trending, reserving, provider reimbursement, and/or risk assessment strategies. You will perform data exploration using a combination of statistical programming languages (including, but not limited to R, Python, SQL, SAS) and deploy predictive analytics and machine learning techniques to improve risk prediction, improve reserve, trend, and financial forecasting in a manner that is actuarially sound, and enable real-time results and operational efficiencies. Additionally, you will develop evaluation and financial reporting standards for internal and external reports, drive efficiency through simplification and automation of pricing factor updates and other processes, and maintain and build dashboards and other visualization tools to discover patterns, send out alerts, and make recommendations to improve pricing accuracy. You will also use machine learning and other analytical techniques to evaluate new and existing pricing factors, present findings, make recommendations, and obtain critical rating model signoffs from senior leaders in actuarial and underwriting. Finally, you will mentor and train junior analysts to ensure knowledge and skillset shared amongst team members.

Responsibilities

  • Develop rating factors and monitor the accuracy of projections.
  • Provide hands-on support and guidance to underwriting stakeholders with quoting.
  • Review and file all required regulatory data in a timely manner.
  • Conduct and develop analysis to assess risk and population risk scores.
  • Develop pricing and trends, assess changes in benefit designs, and develop reserves.
  • Perform forecasting and analyze provider reimbursement terms.
  • Coordinate, prepare, perform, and audit actuarial analyses for complex formulations.
  • Perform data exploration using statistical programming languages like R, Python, SQL, and SAS.
  • Deploy predictive analytics and machine learning techniques for risk prediction and financial forecasting.
  • Develop evaluation and financial reporting standards for internal and external reports.
  • Drive efficiency through simplification and automation of pricing factor updates.
  • Maintain and build dashboards and visualization tools to improve pricing accuracy.
  • Evaluate new and existing pricing factors using analytical techniques.
  • Present findings and recommendations to senior leadership for signoff.
  • Mentor and train junior analysts.

Requirements

  • Bachelor's degree with at least a minor in mathematics, statistics, computer science, or equivalent business experience.
  • Minimum of 3 years of professional actuarial experience.
  • Extensive experience coding with SQL, SAS, or other programming languages.
  • Experience with regression, machine learning, or other complex models.
  • Evidence of customer-facing model or dashboard builds.
  • Comfort presenting ideas and making recommendations to senior leadership.
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