Description

You will drive advanced data science initiatives to solve complex insurance problems.

Responsibilities

• Collect, integrate, and manage structured and unstructured data from internal and external sources.
• Apply advanced statistical and machine learning algorithms (supervised, unsupervised, reinforcement learning) to develop predictive models for risk assessment, fraud detection, and pricing.
• Design and execute model deployment strategies, continuously monitoring performance post-launch.
• Translate analytical findings into clear, actionable insights for business leaders and non-technical stakeholders.
• Provide technical leadership, guidance, and mentorship to junior data scientists.

Required Skills

• 15+ years of overall experience in data science, including a minimum of 5 years in insurance services.
• Strong expertise in Python and R for statistical modeling and ML.
• Advanced proficiency in SQL, including query optimization.
• Hands-on experience with ML frameworks: scikit-learn, TensorFlow, XGBoost, Keras, and PyTorch.
• Proficiency in data visualization tools: Tableau, Power BI, Matplotlib, Seaborn, ggplot2.
• Deep understanding of insurance processes: underwriting, claims, pricing, and risk modeling.
• Proven ability to apply data science to insurance challenges like fraud detection and risk assessment.
• Experience working with cloud platforms: AWS, Google Cloud Platform, or Microsoft Azure.

Key Skills

Education

Any Gradute