Senior Quant Analytics Lead, New Markets (Hybrid)

Athene; Austin (TX); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Athene is seeking an AVP, Quantitative Analytics for New Markets Product, a senior individual contributor focusing on stochastic modeling, insurance guarantees, and 401(k) TDFs. You will collaborate with Product, Asset Management, Derivatives Risk, and Modelling partners under the VP, New Markets Product.

This hybrid role is based in the U.S. with a potential to lead as New Markets grows, and involves heavy quantitative analysis, historical back-testing, and reproducible research tooling in

Qualifications

• 8+ years in quantitative analytics, risk/investment analytics or derivatives modeling.
• Proficiency in Python and SQL for quantitative work; familiarity with Excel, Bloomberg, MATLAB, VBA.
• Experience building reproducible research workflows with version control, testing & traceability.
• Ability to apply AI tools to accelerate research while ensuring validation and risk controls.

Responsibilities

• Design, build, and maintain stochastic models and Monte Carlo engines for New Markets products.
• Conduct derivative pricing and hedge structure valuation for guarantees.
• Generate risk metrics and performance indicators for product design and governance.
• Develop historical back-testing and scenario analysis frameworks; monitor risks across portfolios.

Skills

Python

SQL

Stochastic modeling

Back-testing

Analytics

Critical thinking

Education

Bachelor's in financial engineering

Advanced degree preferred

Tools

Excel

Bloomberg

MATLAB

VBA

Job description

Athene is seeking an AVP, Quantitative Analytics for New Markets Product, a senior individual contributor focusing on stochastic modeling, insurance guarantees, and 401(k) TDFs. You will collaborate with Product, Asset Management, Derivatives Risk, and Modelling partners under the VP, New Markets Product.

This hybrid role is based in the U.S. with a potential to lead as New Markets grows, and involves heavy quantitative analysis, historical back-testing, and reproducible research tooling in