# Quantitative Associate

**Company:** [Corgi Insurance](https://hotfix.jobs/companies/corgi-insurance)
**Location:** Chicago, IL
**Role:** Data Science
**Salary:** $200k – $350k/yr
**Skills:** Statistical Modeling, Forecasting, Optimization, Machine Learning, Predictive Modeling, Risk Modeling, Actuarial Concepts, Data Infrastructure, Cloud-Based Analytics Platforms
**Posted:** 2026-06-05

> Build and maintain quantitative models for insurance pricing, underwriting, forecasting, and investment portfolio management. Requires strong quantitative background and experience with statistical modeling and ML techniques.

## Job Description

## What You'll Do
- Build and maintain quantitative models to support pricing, underwriting, forecasting, and business decision-making.
- Support the Head of Underwriting in the management of the Corgi insurance portfolio and development of underwriting strategy.
- Analyze large and complex datasets to identify insurance trends, risks, and opportunities.
- Partner with engineering and product teams to implement the results of your findings.
- Support the Head of Quantitative Strategy in the management of the Corgi investment portfolio and the development of our investment strategy.
- Design experiments and evaluate outcomes using statistical methods.
- Build and stress-test trade ideas from concept to execution that will directly contribute to the management of the investment portfolio.
- Support strategic initiatives across insurance, operations, finance, and growth.

## What We're Looking For
- Strong quantitative background in mathematics, statistics, economics, physics, computer science, engineering, or a related field.
- Exceptional analytical and problem-solving abilities.
- Familiarity with statistical modeling, forecasting, optimization, or machine learning techniques.
- Ability to communicate complex concepts clearly and effectively.
- Strong intellectual curiosity and willingness to learn new domains quickly.
- Comfortable operating in a fast-moving, ambiguous environment.

## Nice to Have
- Experience in insurance, financial services, capital markets, or other data-intensive industries.
- Exposure to predictive modeling, risk modeling, or actuarial concepts.
- Experience building production analytical tools or models.
- Familiarity with modern data infrastructure and cloud-based analytics platforms.
- Advanced degree in a quantitative discipline.

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