Job Overview
Location
United States
Job Type
Full-time
Category
Data Science
Date Posted
March 24, 2026
Full Job Description
đź“‹ Description
- • The Risk Modeling Lead at SandboxAQ will serve as the definitive technical authority for the company’s risk simulation and financial simulation frameworks, owning the end-to-end lifecycle of probabilistic risk models from research to production deployment. This role is critical to advancing SandboxAQ’s mission of applying Large Quantitative Models (LQMs) to high-impact sectors such as financial services, cybersecurity, and climate resilience, where accurate risk modeling drives strategic decision-making and product differentiation.
- • Day-to-day responsibilities include owning and executing a multi-year technical roadmap for risk modeling, translating advanced stochastic methods into scalable, production-grade analytics; defining rigorous modeling methodologies with full documentation for external review by rating agencies and stakeholders; serving as the primary technical lead in executive briefings and deep-dive workshops to help CROs, CUOs, and senior leadership operationalize model outputs; partnering directly with Product and Engineering teams to integrate research prototypes into cloud-hosted simulation platforms; and driving go-to-market initiatives by articulating model differentiation, use cases, and limitations during RFPs, technical demos, and client engagements.
- • The SAIGE (SandboxAQ AI Generation Engine) team operates at the forefront of AI innovation, rapidly prototyping and validating AI-first SaaS products that leverage SandboxAQ’s proprietary Large Quantitative Models (LQMs) and agentic frameworks. As a global, tech-focused organization spun out of Alphabet Inc. in 2022, SandboxAQ brings together world-class experts in AI, physics, mathematics, engineering, cybersecurity, and medicine to solve complex challenges across industries. The team thrives on high velocity, interdisciplinary collaboration, and a culture of ownership and entrepreneurial impact.
- • In this role, the individual will deepen their expertise in applying cutting-edge stochastic modeling to real-world risk scenarios, gain visibility as a trusted advisor to senior executives and external stakeholders, and contribute to the development of market-differentiating AI-powered risk solutions. They will have the opportunity to shape the technical foundation of SandboxAQ’s risk modeling capabilities, influence product strategy, and work at the intersection of advanced research and enterprise-scale deployment in a mission-driven, high-growth environment.
🎯 Requirements
- • 8+ years of experience building, validating, and deploying probabilistic risk models across natural catastrophes and cyber events.
- • Ph.D. in Computer Science, Physics, Engineering, or a similarly rigorous computational field.
- • Proven expertise in Monte Carlo simulations, multi-parameter probability distribution models, and frequency-severity modeling.
- • Deep technical command of major catastrophe modeling platforms, including RMS (RiskLink), AIR (TouchStone), and KCC (RiskInsight).
- • Demonstrated ability to translate highly technical simulation results for CRO/CUO audiences and senior management.
- • Proficiency in Python and SQL.
🏖️ Benefits
- • Competitive base salary, performance-based incentives or bonuses, and equity participation.
- • Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions.
- • Retirement savings plan with company matching, paid parental leave, and inclusive family-building benefits.
- • Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements.
- • Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.
Skills & Technologies
Python
Senior
Onsite
Degree Required
About SandboxAQ Inc.
SandboxAQ is an enterprise AI company spun out of Alphabet in 2022, focused on applying large quantitative models to solve complex problems in cybersecurity, encryption, sensing, and simulation. Its software and hardware solutions combine AI with quantum-inspired methods to help government and Fortune 500 clients secure data, accelerate materials discovery, and optimize sensing for healthcare and navigation. Based in Palo Alto with global offices, the company partners with large systems integrators and cloud vendors to deploy scalable, physics-aware AI platforms for defense, life sciences, and financial services organizations.
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