Manager/Senior Manager Pricing Modeler

Bean Hr Consulting; Gurugram District; Hybrid; INR 2,000,000 - 3,000,000; Full time

Job summary

Bean Hr Consulting in India seeks a data-driven professional to lead pricing models for property and casualty insurance. You will build GLMs and ML models, design end-to-end pipelines, and translate results into pricing strategies for admitted business.

You will collaborate with actuarial teams, support regulatory filings, and mentor junior analysts while staying aligned with market trends and rigorous governance.

Qualifications

• Bachelor's or Master's in a quantitative field.
• 3–10 years of pricing/modeling experience in the P&C insurance industry.
• Strong GLM experience for pricing or risk segmentation.
• Experience applying ML to insurance pricing (GBMs, random forests, regularized regression).
• Python and/or R proficiency; strong SQL skills.
• Understanding of U.S. market regulatory considerations.
• Affiliation to IAI or IFoA with progress on actuarial exams is a plus.
• Analytical and communication skills; able to explain complex concepts.
• Able to work independently and in a team; detail-oriented.

Responsibilities

• Develop, refine, and maintain pricing and risk models for P&C.
• Build end-to-end modeling pipelines covering data prep and validation.
• Apply ML methods alongside GLMs and benchmark for performance.
• Collaborate with Pricing and Actuarial teams to translate outputs into plans.
• Support rate reviews and regulatory filings with documentation.
• Conduct competitive analysis and market research to align with trends.
• Design and enhance pricing tools and deployment workflows.
• Monitor model performance and recalibrate as needed.
• Present findings to management and stakeholders; mentor juniors.

Skills

GLMs for pricing

Machine Learning

Python

SQL

R

Pricing

P&C Insurance

Model interpretation

Education

Bachelor's/Master's in quantitative field

Tools

Emblem

Radar

SAS

Job description

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