Note: The job is a remote job and is open to candidates in USA. XDuce is recruiting for a leading operations management and analytics company that provides data-driven solutions across insurance and other industries. The Senior Data Scientist will develop, validate, and deploy machine learning and GLM-based pricing models for P&C insurance products, using policy, claims, exposure, and behavioral data. The role partners with actuarial, underwriting, and product teams and supports model governance and regulatory review.
Responsibilities
- Develop machine learning models for various P&C insurance products elated to pricing, customer behavior, retention, price sensitivity, risk segmentation etc
- Build, enhance, and maintain GLM-based pricing models (frequency, severity, pure premium) for insurance products
- Perform model comparison and benchmarking between traditional actuarial models and ML approaches
- Design and implement feature engineering pipelines using policy, claims, exposure, and behavioral data
- Conduct model validation, performance monitoring, and stability analysis over time
- Deploy and operationalize models using Databricks-based workflows
- Partner with actuarial, underwriting, and product teams to translate business problems into analytical solutions
- Document modeling methodology, assumptions, and results to support model governance and regulatory review
Skills
- • Location - Based out of US (REMOTE)
- • 7+ years of experience in P&C insurance analytics, pricing, or actuarial-adjacent Data Science roles with proficiency in advanced Machine Learning, NLP, DL techniques
- • Hands-on, end-to-end ownership mindset from data preparation to model deployment
- • Proven ability to work with large, complex insurance datasets with the ability to explain analytical results to non-technical stakeholders
- • Strong understanding of P&C insurance pricing concepts, customer life cycle, rating variables, and risk segmentation
- • Bachelors or Master's degree in data science, economics, mathematics, computer science/engineering, operations research or related analytics areas
- • Machine Learning algorithms for tabular data (Gradient Boosting, Random Forests, XGBoost, LightGBM, NLP-Unstructured)
- • GLM modeling expertise (Poisson, Gamma, Tweedie, Logistic)
- • Python for data analysis and modeling (pandas, numpy, scikit-learn, statsmodels)
- • Databricks / Spark (PySpark) for large-scale data transformation and feature engineering
- • SQL for data extraction, transformation, and analytical queries
- • Model explainability techniques (e.g., SHAP, partial dependence)
- • Experience with model deployment, scoring pipelines, and performance monitoring
Benefits
- An exciting, fast-paced and innovative environment with opportunities to influence business decisions
- Opportunity to work closely with highly experienced, world-class analytics consultants from the first day
- Learning opportunities covering various aspects of clients' businesses
- Development of effective teamwork and time-management skills for personal and professional growth
- Training in all aspects of analytics and in leading analytical tools and techniques
- Guidance and coaching through a mentoring program, wherein every junior-level employee is assigned a senior-level professional as an advisor
- Opportunities for further growth and development within the company and beyond
Company Overview
Company H1B Sponsorship