Top Tech Jobs & Startup Jobs in Chicago, IL

Lead North Carolina high-net-worth P&C product and pricing strategy, manage NCRB/NCRF filings and regulatory requirements, drive profitable growth, partner with actuarial/underwriting/legal/compliance, represent the company to regulators, and mentor product team members to deliver market-responsive product solutions.

The VP, Head of Actuarial Pricing will lead pricing strategies and modernization efforts, driving business growth through sophisticated data-driven approaches and strong team leadership in P&C pricing.

The VP, Head of Actuarial Reserving oversees the loss reserving framework, provides actuarial opinions, ensures compliance, and leads the actuarial team. Responsibilities include financial reporting, regulatory compliance, risk assessment, and governance in reserving practices while collaborating with various departments.

Lead state-specific actuarial pricing for major markets, partner cross-functionally to drive profitability and growth, support rate filings and regulatory interactions, enhance pricing methodologies and tools, analyze trends and exposures, and mentor actuarial analysts through the rate filing process.

The Associate Product Manager will support state-specific strategies for high-net-worth personal insurance products, analyze KPIs, handle rate plans, collaborate cross-functionally, and ensure regulatory compliance.

The Senior Product Development Analyst supports product innovation and management by developing features, conducting research, collaborating with teams, and assisting in training and decision-making processes.

Lead state-level P&C product strategy and a team of analysts to drive growth and underwriting margin. Manage product roadmaps, rate review and filing processes, regulatory relationships, cross-functional partnerships, competitive monitoring, and member experience. Mentor staff, serve as subject-matter expert at hearings and panels, and provide strategic guidance on pricing, product changes, and implementation.

Lead and scale a production-focused data science practice: define engineering standards, build reusable Python frameworks, drive end-to-end model development and monitoring, collaborate with Data Engineering/MLOps/analytics and business partners, mentor team members, and establish measurement, documentation, and prioritization disciplines to ensure models deliver business impact across Claims, Underwriting, Risk, and Distribution.