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Lead Risk Analytics Consultant

India, Bengaluru · Job Posted May 14, 2026
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Job Description

Wells Fargo is seeking an experienced Lead Risk Analytics Consultant to join its Risk Analytics team at Bangalore. This role sits at the intersection of quantitative modeling, data analytics, and stakeholder engagement, supporting enterprise-wide credit risk management and regulatory objectives.

Job Responsibility

  • Perform quantitative modeling and advanced data analysis to generate decision-useful insights across credit risk portfolios
  • Lead or contribute to moderately to highly complex initiatives, delivering analytics, forecasts, and risk strategies aligned with enterprise risk objectives
  • Develop, review, and maintain credit risk models (e.g., PD, LGD, EAD, stress testing, portfolio analytics), with exposure to Securities-Based Lending (SBL) considered a strong advantage
  • Review and analyze data aggregation, forecasting, reporting, and programming models, ensuring accuracy, robustness, and scalability
  • Own end-to-end model processes, including data reconciliation, production monitoring, documentation, and governance in line with internal policies and regulatory expectations
  • Partner with Model Risk Management / Model Validation, Compliance, and Technology teams to address model findings, remediation, and implementation issues
  • Resolve complex data, production, and business modeling challenges, applying sound judgment and risk discipline
  • Lead project workstreams, mentor junior analysts, and contribute to building a strong risk analytics talent pipeline
  • Collaborate with cross-enterprise risk teams to develop common modeling standards, frameworks, and best practices
  • Lead complex initiatives related to business analysis and modeling, including those that are cross functional, with broad impact, and act as key participant in data aggregation, monitoring, and reporting of stress testing and portfolio analysis for Risk Analytics
  • Review and analyze complex programing models to extract data and manipulate databases to provide statistical and financial modeling specific to businesses supported
  • Manage the roll out of pilot programs developed as a result of programmed models for supported businesses and product line
  • Make decisions in complex product strategies, data modeling, and risk exposure, requiring solid understanding of business unit projects and regulatory responses, policies, procedures, and compliance requirements that influence and lead Analytic and Reporting to meet deliverables and drive new initiatives
  • Collaborate and consult with peers, less experienced to more experienced managers, to resolve production, project, and regulatory issues, and achieve risk analysts, and common modeling goals
  • Lead projects, teams, and mentor

Requirements

  • 4+ years of experience in Risk Analytics, Quantitative Risk, Credit Risk, or a related field
  • Demonstrated experience through a combination of work experience, education, or advanced training

Nice to have

  • 8+ years of overall professional experience, with significant exposure to risk analytics or quantitative finance
  • Strong background in Credit Risk Modeling and knowledge of retail, wholesale, or secured lending portfolios
  • Hands-on programming experience in Python
  • familiarity with large datasets and data pipelines
  • Experience working with Securities-Based Lending (SBL) or secured financing products is a strong plus
  • Proven ability to extract, clean, and analyze complex datasets to support risk monitoring, forecasting, and regulatory reporting
  • Experience partnering with business, risk, technology, and model review teams in a regulated financial environment
  • Ability to translate complex analytical results into clear, actionable insights for senior and mid-level stakeholders
  • Strong understanding of model governance, regulatory expectations, and documentation standards
  • Certifications such as FRM, CFA, PRM, or CQF are highly desirable
  • Exceptional attention to detail, strong problem-solving mindset, and comfort working with large volumes of data
  • Excellent oral and written communication skills, including the ability to present technical concepts to non-technical audiences
  • Ability to thrive in a fast-paced, deadline-driven environment

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