Description

You will build and maintain production-grade machine learning models for risk, claims, and fraud analytics, leveraging NLP and operations research to drive decisioning.

This role is on-site.

Responsibilities

• Develop predictive models for incident prediction, severity modeling, and risk scoring using Python and Spark.
• Implement Explainable AI techniques (SHAP, LIME) to ensure model transparency and regulatory compliance.
• Build and optimize NLP pipelines and LLM applications for claims and incident narrative analysis.
• Design and solve optimization problems using Linear, Integer, and Mixed Integer Programming (CPLEX/Gurobi) for resource allocation.
• Deploy, monitor, and manage model drift for ML systems in enterprise environments.

Required Skills

• 5+ years in Data Science, ML, NLP, or Operations Research (2+ years with relevant PhD).
• Strong proficiency in Python, SQL, and Spark for large-scale data processing.
• Experience with Databricks and Snowflake for data engineering and architecture.
• Proven track record of building and deploying production ML systems.
• Knowledge of data governance and PII handling in enterprise settings.
• Familiarity with AI/ML frameworks and Explainable AI tools.
• Experience in risk, claims, fraud, or incident analytics domains.
• Agile delivery experience in a professional setting.

Preferred Skills

• PhD in Computer Science, Statistics, Industrial Engineering, or Operations Research.
• Experience in hospitality or travel industry analytics.

Key Skills

Education

Master's degree