Lincoln Financial

AVP, Quantitative Investment Analysis Management

Lincoln Financial

full-time

Posted on:

Location Type: Hybrid

Location: Radnor • Connecticut • North Carolina • United States

Visit company website

Explore more

✨ AI Apply
Apply

Salary

💰 $135,000 - $225,000 per year

Job Level

Lead

Tech Stack

AWSNumpyPandasPythonSQL

About the role

  • Build the SAA & ALM analytics platform
  • Familiarity and experience managing code using GitLab and deploying python code on AWS
  • 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
  • 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
  • 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
  • Work across the Investments team to partner with insurance business units, ALM, Actuarial, Enterprise Risk Management, and Finance

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Financial Engineering, or related discipline (Master’s degree preferred)
  • 5+ years of professional software engineering or data engineering experience in investment/insurance or adjacent risk/quant domains
  • Demonstrated track record building production data/analytics platforms supporting portfolio construction or risk/ALM
  • 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)
  • Fluent in multiple languages with depth in Python and SQL (required)
  • 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
  • Practical familiarity with NAIC investment regulations, statutory accounting and reporting (including RBC capital concepts and statutory investment schedules)
Benefits
  • 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonSQLdata engineeringrelational modelingperformance tuningdata integrationorchestrationtesting frameworksobservabilityquant/optimization toolkit