Advanced Analytics Specialist

About the Team 

The Enabling Advanced Analytics team is part of Business Excellence within P&C Re Operations. The team is responsible for developing and maintaining the P&C Re Operations analytics landscape, supporting functions such as Underwriting Operations, Technical Accounting & Claims Operations, Claims Management, In-force Management, and Client Audit. 

We generate actionable business insights by applying advanced analytics, automation, and AI-driven solutions, and act as a bridge between business and IT.  

About the Role 

Looking for a Senior Data Scientist to work on solving high-priority business problems using data-driven approaches and advanced analytics. This role is based in Bangalore and will work closely with the Advanced Analytics Lead, team members, IT/D&T, and senior business stakeholders.  

You will independently own and deliver complex analytics initiatives end-to-end, contribute to the evolution of our analytics and AI platform, and help scale solutions from exploratory PoCs to robust, production-ready capabilities with measurable business impact. 

Key Responsibilities 

• Translate business needs into well-defined analytical problem statements and develop data-driven solutions. 

• Apply statistical, algorithmic, data mining, and visualization techniques to generate business insights. 

• Deliver end-to-end data science solutions, from PoC development to production deployment, working closely with business and IT team 

• Identify data gaps and propose improvements to the data collection processes. 

• Take ownership of projects, manage stakeholders effectively, and deliver innovative solutions. 

About You 

Technical Skills 

• Master’s degree in quantitative field (STEM, Economics, Statistics, Engineering, or similar). 

• Minimum 8 years of hands-on experience in building data science solutions. 

• Strong foundation in statistics and probability. 

• Strong practical expertise in classical machine learning techniques, such as parametric algorithms (linear/logistic regression), ensemble methods (decision trees, random forests, XGBoost/LightGBM), clustering (k-means, hierarchical clustering), and dimensionality reduction (PCA), with experience in feature engineering, hyperparameter tuning, and model evaluation. 

• Hands-on experience with NLP and applied Generative AI use cases (e.g., LLMs, prompt engineering, RAG). 

• Proficiency in Python and Spark (PySpark); experience with common ML/AI libraries. 

• Preferred: SQL, Python, Power BI; insurance/reinsurance domain exposure. 

Soft Skills 

• Clear and concise communicator (written and verbal), able to tailor communication to technical and non-technical audiences. 

• Strong problem-solver with a consulting mindset and the ability to work effectively with ambiguity. 

• Comfortable operating in a matrix organization and influencing stakeholders without formal authority.