Description

You will design, develop, and deploy machine learning models for risk assessment, pricing, claims analytics, and portfolio optimization.

This role is hybrid.

Responsibilities

• Apply advanced statistical and ML techniques including regression, classification, clustering, and time-series forecasting.
• Lead data exploration, feature engineering, and model validation to ensure accuracy.
• Build and optimize data pipelines and ETL processes for large-scale analytics.
• Deploy and operationalize models on AWS or Azure, ensuring scalability.
• Mentor junior data scientists and promote ML best practices.

Required Skills

• 7+ years of experience in data science or machine learning.
• Strong proficiency in Python, SQL, Pandas, and NumPy.
• Extensive experience with statistical modeling and ML techniques.
• Hands-on experience with data visualization tools like Power BI or Tableau.
• Working knowledge of big data technologies such as Spark and Hadoop.
• Experience deploying ML models on AWS or Azure.
• Solid understanding of insurance and reinsurance concepts.

Preferred Skills

• Strong problem-solving and analytical thinking capabilities.
• Ability to manage multiple initiatives and prioritize effectively.

Key Skills

Education

Any Gradute