Description

You will leverage data to drive insights into risk modeling, pricing strategies, claims analysis, and portfolio optimization within the reinsurance domain.

Responsibilities

• Develop statistical models and machine learning algorithms including regression, classification, clustering, and time series forecasting.
• Build and manage ETL processes, data wrangling, and feature engineering workflows.
• Deploy models and data pipelines using cloud platforms.
• Communicate complex technical findings and data storytelling to non-technical stakeholders.
• Collaborate with cross-functional teams including actuarial, underwriting, and IT.

Required Skills

• 5+ years of experience in data science or machine learning roles.
• Proficiency in Python with expertise in Pandas, NumPy, and Scikit-learn.
• Strong SQL skills for data manipulation and extraction.
• Experience with Spark and Hadoop for big data processing.
• Hands-on experience with ETL processes and data engineering.
• Working knowledge of Azure or AWS for model deployment and pipelines.
• Competency in data visualization using Power BI.
• Ability to apply statistical modeling to risk assessment and claims analytics.

Preferred Skills

• Experience with NLP, Monte Carlo simulations, or stochastic modeling.
• Familiarity with Git, CI/CD pipelines, or geospatial mapping tools.
• Knowledge of R, SAS, or regulatory frameworks like Solvency II and IFRS 17.

Key Skills

Education

Any Gradute