Role & Responsibilities:

- Develop, refine, and maintain pricing and risk models for P&C; insurance products using both Generalized Linear Models (GLMs) and machine learning techniques, with a focus on personal lines auto and homeowners.

- Build end-to-end modeling pipelines covering data preparation, feature engineering, variable selection, model fitting, validation, and performance monitoring on large policy and claims datasets.

- Apply machine learning methods such as GBMs (XGBoost/LightGBM), random forests, and penalized regression alongside traditional GLMs, and blend or benchmark approaches to improve lift, stability, and interpretability.

- Collaborate with the Pricing and Actuarial teams to translate model outputs into rating plans, pricing strategies, and rate indications for admitted business.

- Support rate reviews and regulatory filings by producing model documentation, exhibits, and defensible explanations of model structure and variable effects.

- Conduct competitive analysis and market research to keep pricing models aligned with market trends, loss cost developments, and regulatory changes.

- Design and enhance pricing tools, model deployment workflows, and analytical assets to streamline and automate pricing processes.

- Continuously monitor model performance in production, diagnose degradation or dislocation issues, and recommend recalibration or redevelopment where needed.

- Present modeling findings and recommendations to management, underwriters, product managers, and client stakeholders in a clear, business-oriented manner.

- Mentor and review the work of junior analysts, and contribute to best practices in modeling standards, documentation, and governance.

Candidate Profile:





- Bachelor's/Master's degree in engineering, economics, mathematics, actuarial science, statistics, data science, or a related quantitative field. (Required)

- 3-10 years of pricing/modeling experience in the P&C; insurance industry, with hands-on model development ownership. (Required)

- Strong experience building GLMs for pricing or risk segmentation (frequency/severity, pure premium, loss ratio models). (Required)

- Proven experience applying machine learning techniques such as GBMs (XGBoost/LightGBM), random forests, or regularized regression to insurance pricing or related problems. (Required)

- Experience in personal lines, particularly auto and/or homeowners pricing. (Strongly preferred)

- Proficiency in Python and/or R for statistical modeling and machine learning, along with strong SQL skills for data extraction and manipulation. (Required)

- Working knowledge of pricing platforms and tools such as Emblem, Radar, SAS, or equivalent. (Preferred)

- Understanding of admitted business, rate filings, and the regulatory considerations that shape model design and documentation in the U.S. market. (Preferred)

- Affiliation to IAI or IFoA with progress on actuarial exams will be an added advantage.

- Excellent analytical and problem-solving skills, with the ability to work with large, messy datasets and make data-driven decisions.

- Strong communication skills, including the ability to explain complex GLM and ML concepts to both technical and non-technical stakeholders.

- Ability to work independently and collaboratively in a team-oriented, client-facing workplace.

- Detail-oriented with strong organizational and time management skills, and able to adapt to changing priorities in a fast-paced environment.

📌 Manager/Senior Manager Pricing Modeler (Gurugram)
🏢 Bean HR Consulting
📍 Gurugram