Vice President, Asset Analytics – Remote

Symetra is seeking a strategic and highly effective senior leader to serve as Vice President, Asset Analytics. This role leads the strategy, prioritization, governance, and communication of the enterprise asset analytics function — the team responsible for enterprise asset modeling, asset-liability management (ALM), asset optimization, economic assumption setting, asset-related financial planning support, and associated reporting across the Actuarial Division and beyond.

About the role

Reporting to the Chief Actuary, this leader will set direction, establish decision standards, and provide oversight for the asset analytics organization — while also maintaining strong technical credibility and engagement in the work itself.

This is first and foremost a leadership role: setting vision, modernizing capabilities, building talent, clarifying ownership boundaries, and ensuring senior executives receive clear, confident explanations of complex asset results.

The Asset Analytics team is responsible for:

• Enterprise asset modeling across the full balance sheet
• Enterprise ALM reporting and support
• Financial planning and analysis for invested assets
• Asset optimization analysis
• Economic and capital market assumption setting
• Asset-related reporting and performance attribution
• Knowledge-sharing across Actuarial, Investments, Finance, and senior leadership

What You will Do

• Lead the enterprise asset analytics function with responsibility for both strategic direction and technical excellence. Set the vision and operating model for the team while ensuring delivery of high-quality asset modeling, ALM analytics, and optimization capabilities that inform financial planning, capital management, pricing, and enterprise decision-making.
• Build and develop a diversified team of asset modelers, quants, and analytics professionals, incorporating skills that extend beyond traditional actuarial backgrounds to include structured credit expertise, quantitative finance, and data analytics. Establish clear training pathways, strengthen technical depth, and foster a culture of accountability and continuous improvement.
• A core mandate of the position is modernization — moving the function from model production to scalable insight generation. This includes replacing manual processes with production-ready workflows, enhancing data visualization and self-service analytics, and defining clear boundaries between standardized modeling, optimization exercises, and customized analyses.
• Implement a formal governance framework for asset models and analytics, establish structured enterprise-wide intake and prioritization processes for ad hoc requests, and clarify roles and responsibilities across ALM, Valuation, FP&A, and Investments consistent with industry standards.
• Oversee development of enterprise models of asset cash flows, book values, and market values across all asset classes. Responsibilities include ALM analytics, asset optimization modeling incorporating regulatory capital impacts, oversight of actuarial valuation models for custom private assets and derivative hedges, development of mapping methodologies for structured assets, investigation of model drivers, and preparation of clear explanations of Statutory and GAAP investment performance versus plan and prior periods. Be a thought leader for general strategic conversations related to portfolio composition and performance.
• Translate complex quantitative outputs into concise, decision-ready insights and serve as a trusted strategic thought partner to senior and executive leadership.
• Work closely with and cultivate a strong relationship with the Head of Portfolio Management.

What Success Looks Like

• A clearly defined and well-governed asset analytics function.
• Strong executive confidence in asset projections and explanations.
• Solid partnerships and credibility across the organization including with the Head of Portfolio Management, the head of Investments Accounting, and the Life & Annuity line actuaries.
• Scalable, modernized modeling platforms with reduced manual processes.
• Effective intake and prioritization of ad hoc requests.
• A diversified, high-performing quantitative team with strong development pathways.