Description

Design, deploy, and maintain machine learning models for risk assessment, pricing, and portfolio optimization.

This role is on-site.

Responsibilities

• Build and optimize data pipelines and ETL processes for large-scale analytics.
• Apply statistical and ML techniques including regression, classification, and time-series forecasting.
• Develop interactive dashboards using Power BI, Tableau, or Python libraries.
• Operationalize models on AWS or Azure, ensuring scalability and performance.
• Mentor junior data scientists and enforce data governance and compliance standards.

Required Skills

• 10+ years of experience in data science, machine learning, or AI engineering.
• Strong proficiency in Python, SQL, Pandas, NumPy, and Scikit-learn.
• Hands-on experience with Power BI, Tableau, Matplotlib, or Seaborn.
• Working knowledge of big data technologies: Spark, Hadoop.
• Experience deploying data pipelines and ML models on AWS or Azure.
• Solid understanding of insurance/reinsurance concepts: actuarial models, risk assessment, claims analytics.

Preferred Skills

• Experience with R or SAS.
• Exposure to NLP, geospatial analytics, Monte Carlo simulations, or stochastic modeling.
• Familiarity with CI/CD pipelines, Git, and MLOps practices.

Key Skills

Education

Bachelor's degree