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hyperexponential is an AI-powered platform serving the $7 trillion insurance industry, enabling critical decisions around risk assessment and pricing. Backed by a16z, Highland Europe, and Battery Ventures, the company is trusted by nearly 50 of the world's largest insurers with zero churn and billions in premiums flowing through the platform.
The Delivery Engineering team is a specialized group of engineers, actuaries, mathematicians, and data scientists who tackle the most complex and interesting problems customers face. Rather than traditional transformations, the team focuses on challenges requiring deep technical expertise, market knowledge, and platform mastery.
In this role, you will own end-to-end model delivery on the hx platform, from scoping and build through testing, iteration, and customer delivery. You'll build and maintain production-grade Python models using modern engineering and modeling practices. You'll work directly with customer actuarial teams and internal stakeholders to solve complex, ambiguous modeling and coding problems. You'll raise quality across the team through code review, testing, and contributions to best-practice model development guidance. You'll support and mentor junior model developers through pairing, feedback, and day-to-day delivery support. You'll continuously look for ways to improve model development standards, tooling, and ways of working.
The role is based in London on a hybrid basis, working from The Ministry office with regular in-person collaboration.
REQUIREMENTS:
- Shipped and maintained production-grade Python code in complex or data-heavy environments
- Applied predictive modeling or advanced analytics in real-world settings (insurance or reinsurance exposure is a bonus, not a requirement)
- Taken ownership of ambiguous problems, creating structure and driving them through to high-quality outcomes
- Worked directly with non-technical stakeholders or customers, translating requirements into robust technical solutions
- Operated effectively in a high-trust, high-accountability environment, proactively driving your own development and learning
You're unlikely to thrive here if you prefer following detailed instructions rather than experimenting, are uncomfortable working directly with non-technical stakeholders, or avoid tackling ambiguous or open-ended problems.
