CCB Risk Modeling Data-Scientist Sr Associate Fraud Prevention
JPMorgan Chase & Co. (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted 21h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop, train, deploy, and monitor machine learning models focused on fraud prevention and risk management in a financial institution context.
- Lead technical strategy, mentor junior team members, and collaborate cross-functionally to align modeling solutions with business objectives.
- Innovate with advanced techniques including Graph Networks, Agentic AI, Large Language Models, and AI agents, using AWS and tools like Databricks and PySpark.
Minimum Requirements
- Master's degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field, or equivalent experience.
- Minimum 5 years of experience developing and managing predictive risk models in financial institutions.
- Proficient in Python, SQL or PySpark; experience with deep learning frameworks (PyTorch or TensorFlow) and classical ML tools (XGBoost, Scikit-learn).
- Experience working with large datasets, data pipelines, AWS cloud environments, and ability to build/test AI agents for reliability.
Ideal Candidate Profile
- Strong expertise in both classical and deep learning methods with understanding of underlying mathematics behind algorithms.
- Able to lead innovation in fraud detection using emerging technologies like Graph Analytics and Agentic AI, with preference knowledge of GSQL.
- Experience in delivering scalable, reusable ML solutions contributing to firmwide capabilities and taking product responsibility for models impacting live financial transactions.