Data Scientist

Role: Data Scientist

Remote

Role & Responsibilities Overview:

·        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

Candidate Profile:

·        Location - Based out of US, (Cincinnati, Ohio Preferred)

·        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

Technical skills:

·        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

What we offer:

• EXL Analytics offers an exciting, fast paced and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world class analytics consultants.

• You can expect to learn many aspects of businesses that our clients engage in. You will also learn effective teamwork and time-management skills - key aspects for personal and professional growth
• Analytics requires different skill sets at different levels within the organization. At EXL Analytics, we invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques.

• We provide guidance/ coaching to every employee through our mentoring program wherein every junior level employee is assigned a senior level professional as advisors.
• Sky is the limit for our team members. The unique experiences gathered at EXL Analytics sets the stage for further growth and development in our company and beyond