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Wells Fargo is seeking a Lead Risk Analytics Consultant
Job Responsibility:
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
Model Selection & Evaluation: Assess business use case requirements and recommend suitable Gen AI models and platforms
Architecture & Integration: Design AI solution architecture that is aligned to enterprise expectations and integrates with existing enterprise systems. Support decisions around APIs, data pipelines, orchestration layers, UI/UX, etc
Data Preparation & Governance: Collaborate with data teams to ensure high-quality, compliant datasets. Implement data governance and processing standards
Model Fine-Tuning & Optimization: Fine-tune base models for domain-specific tasks. Optimize for latency, accuracy, and resource utilization
Performance Monitoring & Feedback Loop: Define KPIs for AI solutions. Continuously monitor and improve models based on feedback
Business Enablement & Advisory: Act as AI consultants for business teams. Provide training and documentation for AI adoption
Lead and influence assessment of business use cases and GenAI model/platform selection through a model risk and enterprise governance lens
Provide final risk recommendations and approvals for AI model usage aligned with enterprise risk frameworks
Demonstrated ability to lead complex risk analytics initiatives and influence senior stakeholders
Strong understanding of risk analytics, model risk management, and enterprise control frameworks
Working knowledge of Generative AI concepts, architectures, and AI lifecycle risks
Experience partnering with technology and data teams in regulated environments
Strong analytical, communication, and stakeholder management skills
Deliver 100% quality and SLA compliance on executions
Drive discussions with stakeholders
Requirements:
5+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5 - 10+ years of experience in risk analytics, model risk, or technology risk, including leadership or lead‑level responsibilities
Bachelor's or Master's degree in Risk Management, Data Science, Analytics, Engineering, or related field
Experience leading cross‑functional risk initiatives involving AI, data, and technology teams
Experience in risk analytics, model risk, AML/credit/operational risk, or advanced analytics roles
Working knowledge of AI/ML and Generative AI concepts, including model lifecycle risks, bias, explainability, and performance monitoring
Advanced degree (MBA, MS, or equivalent) in Risk Management, Analytics, Data Science, Engineering, or a related quantitative field
Strong experience in risk analytics, model risk management, or technology risk within a regulated or enterprise environment
Experience collaborating with AI, data, and engineering teams to assess risks, define controls, and establish governance standards
Excellent stakeholder and communication skills, with the ability to translate technical AI risks into clear business insights
Ability to work in a dynamic environment and adjust to changing priorities
Ability to work at the approved locations in the job posting