Saenger Associates is seeking an entrepreneurial minded Senior Actuary/Principal with deep expertise in Medicaid, actuarial theory, and affordable care act (ACA) for our client. The ideal candidate will have a strong business development background and, ideally, an existing client base to grow with our client. This is an opportunity to join a well-established firm with a 20+ year reputation in actuarial consulting while benefiting from a highly skilled support system.
Key Responsibilities • Lead and oversee Medicaid actuarial projects, including rate setting, risk adjustment, and financial modeling. • Drive business development efforts, securing new engagements and expanding relationships with existing clients. • Leverage your industry network to bring new opportunities to our client and contribute to revenue growth. • Mentor and develop junior actuaries, ensuring high-quality deliverables and adherence to actuarial best practices. • Collaborate with regulatory agencies and clients on state and federal Medicaid initiatives. • Utilize our client's robust actuarial models and data analytics tools to deliver superior client solutions.
Required Qualifications: • Fellow of the Society of Actuaries (FSA) or Associate (ASA) with significant experience • 10+ years of actuarial experience with a focus on Medicaid and healthcare consulting • Proven business development experience, with a history of securing and managing client relationships • Strong understanding of actuarial principles, risk adjustment, and payment models • Experience working with state Medicaid agencies, managed care organizations (MCOs), and CMS • Excellent leadership, communication, and project management skills • Background in mathematics, actuarial science, statistics, computer science, or related fields
Preferred Qualifications: • Existing book of business or strong industry relationships that can generate new opportunities • Experience with alternative payment models, value-based care, and actuarial certifications • Knowledge of data analytics and predictive modeling techniques