Lead Quantitative Analytics Specialist - Python, SQL, Machine Learning Model Building, Gen AI
Wells Fargo (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 28–44 LPA
Posted 9h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead end-to-end development, implementation, validation, and monitoring of advanced fraud risk models using statistical and machine learning techniques.
- Design, deploy, and improve fraud detection models across multiple risk domains including card transactions, applications, and payments.
- Lead multiple fraud analytics projects, set model development standards, mentor junior analysts, and collaborate with stakeholders to translate insights into business actions.
Minimum Requirements
- 5+ years of quantitative analytics experience or equivalent through work/training/education.
- Bachelor's degree or higher in quantitative disciplines like mathematics, statistics, engineering, physics, economics, or computer science.
- Hands-on experience building machine learning models using Python and SQL; experience with Generative AI technologies applied to analytics or business use cases.
- Ability to work 1:30 PM to 10:30 PM IST shift; hybrid work environment as per business needs.
Ideal Candidate Profile
- Demonstrated expertise in fraud analytics, financial crimes risk, or related advanced analytics applied in fraud detection.
- Experience working with large-scale data in cloud environments along with knowledge of model deployment, MLOps, or model lifecycle practices.
- Proven ability to lead complex analytics initiatives, manage model governance requirements, and communicate technical insights effectively to diverse stakeholders.