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. 25–45 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead development, implementation, validation, documentation, and ongoing monitoring of complex fraud risk models using advanced statistical and machine learning techniques.
- Design and deploy fraud detection models across multiple fraud risk domains including card transactions, applications, checks, and payments.
- Lead multiple fraud analytics initiatives, provide technical direction, mentorship, and collaborate with cross-functional stakeholders to translate analytics into business actions.
Minimum Requirements
- 5+ years of Quantitative Analytics experience or equivalent.
- Bachelor's degree or higher in a quantitative discipline (mathematics, statistics, engineering, physics, economics, or computer science).
- Hands-on experience with Python and SQL for data analysis and quantitative modeling.
- Experience building, developing, or implementing machine learning models; experience with Generative AI technologies.
Ideal Candidate Profile
- Experienced in applying machine learning and advanced analytics specifically within fraud, financial crimes, or risk domains.
- Skilled at working with large-scale data and cloud environments, familiar with model deployment and lifecycle (MLOps) practices.
- Able to collaborate effectively with model risk management and business teams, translating complex analytics into actionable insights.