Assistant Vice President, Strategic Asset Allocation Analytics

Lincoln Financial•Radnor, PA

8d•$171,375 - $274,200•Hybrid

About The Position

Lincoln’s Investment Strategy & Portfolio Management team is evolving its Strategic Asset Allocation (SAA) and asset liability modeling toolkit to better support enterprise risk appetite, capital, liquidity, and new business growth across U.S.A. and Bermuda entities. The team partners with insurance businesses and the Investments team to design and maintain the enterprise SAA across legal entities, integrating new business pricing with in force optimization, and operating within U.S. and Bermuda regulatory regimes. In this role, you will own the quantitative modeling and analytics that power strategic asset allocation, in-force optimization, and new business pricing support — drawing on ALM analytics as a key input, and building select ALM components as needed. You will work as a close quantitative partner to investment strategy and portfolio management, bringing deep understanding of SAA and portfolio construction to develop models and dashboards, and ensuring our analytics incorporate regulatory requirements for NAIC and Bermuda Monetary Authority standards. Your efforts will enable our investment strategies to be produced faster across regimes and improve our documentation and governance controls.

Requirements

Fluent in multiple languages with depth in Python and SQL (required). You also bring working proficiency in other languages for legacy model integration.
Hands on experience building scalable, object-oriented solutions/components for model enhancements/extensions across different products/assumptions. Enhancing existing core framework to scale model with change requests from product owners (annuities, life, group etc.) while maintaining code readability, documentation, and audit trail.
Hands on data engineering: relational modeling, performance tuning, data integration (with tools like Bloomberg & Intex), orchestration, version control, testing frameworks, and observability.
Quant/optimization toolkit experience (e.g., pandas, NumPy, SciPy, Pyomo/OR Tools) and time series/scenario modeling.
Code testing/automation using CI/CD framework, Backtesting of strategy – creating backtesting data and summarizing model results and reporting Investment analytics by potentially leveraging Lincoln’s AI tools/suite of products.
Practical familiarity with NAIC investment regulations, statutory accounting and reporting (including RBC capital concepts and statutory investment schedules)
Understanding of Bermuda Monetary Authority capital and reporting
Deep understanding of SAA optimization incorporating the matching of insurance product liability cash flows across multiple economic scenarios
Exposure to ALM and insurance balance sheet dynamics (duration/convexity, liquidity ladders, reinvestment, asset rating migration).
Comfort integrating third party and internal data sources (e.g., pricing/spread inputs, cash flow engines) into reproducible SAA processes.
Product mindset: ability to decompose ambiguous strategy problems into small, testable engineering increments with clear documentation.
Excellent communication with non engineers; able to explain model assumptions, caveats, and results succinctly for decision makers.
Bachelor’s degree in Financial Engineering, Mathematics, Quantitative Finance, Actuarial Science, Computer Science, Engineering, or related discipline (Master’s degree, CFA, or FRM preferred).
10+ years of experience within the financial services or related industry; 5+ years of professional experience in quantitative investment strategy, strategic asset allocation, portfolio construction, or asset-liability management, with strong hands-on software/data engineering skills to build and productionize the underlying analytics.
Demonstrated track record building production data/analytics platforms supporting portfolio construction or risk/ALM.

Nice To Haves

Experience in producing asset cashflows utilizing tools like Factset/Bloomberg/Intex is a plus.

Responsibilities

Build and own the SAA analytics platform: Engineer reliable Python services and SQL backed data pipelines that ingest asset, liability, and market data; orchestrate runs; and expose results to strategy and risk partners (APIs, notebooks, dashboards). Productionize research prototypes into hardened components (configuration management, unit/integration tests, logging, lineage, and automated documentation) supporting enterprise wide SAA across U.S. and Bermuda entities.
Portfolio construction & optimization enablement: Implement and scale optimization, scenario analysis, and stress testing tools used to construct SAA under capital, rating, liquidity, and ALM constraints; parameterize for both U.S. RBC and Bermuda BSCR frameworks. Integrate cash flow projections (e.g., BondEdge outputs) and reconcile them to portfolio views with auditable data controls.
Regulatory aware data modeling: Model and map security master and position data to NAIC designations and statutory schedules and to BMA BSCR asset categories and SBA portfolios; embed validation checks aligned to reporting rules.
Partner across the enterprise: Work across the Investments team to partner with insurance business units, ALM, Actuarial, Enterprise Risk Management, and Finance.