Sr. Manager, Risk Practice

Visa Visa · Fintech · Mumbai, India, IN

Visa is seeking a Sr. Manager for their VCA Credit Risk Advisory team in Mumbai. This role involves providing advisory services to clients on Credit Risk and Portfolio Optimization, developing consulting services across Asia Pacific, and contributing to client engagements. Responsibilities include understanding business problems, business development (proposals, project plans), end-to-end project delivery, maintaining documentation and quality, and developing consulting practice materials. The ideal candidate has 10+ years of risk experience in banking/consumer lending, a quantitative degree, deep domain expertise in Credit Risk Management, and understanding of credit risk models, decisioning strategies, and regulatory frameworks. Proficiency in statistical techniques like regression, decision trees, and neural networks is preferred.

What you'd actually do

  1. Contribute to the delivery of Credit Risk advisory engagements across Asia Pacific
  2. Collaborating with the client’s team (both internal and external) to understand the business problem and desired business outcome
  3. Business Development: Prepare client proposals and project plans, identifying dependencies, roles and responsibilities, scope, and deliverables.
  4. End-to-end delivery of multiple projects within timelines, scope and budget requirements
  5. Ensuring all project documentation is up to date and maintain the highest levels of quality in deliverables
  6. Support the development and maintenance of consistency, standards and quality control of Credit Risk consulting methodologies, ensuring world-class best practices and efficiency through economies of scale.
  7. Thought Leadership, Practice, and Solution Development: Create consulting practice materials such as set-plays, pitch decks, whitepapers and other assets following best practices and the latest IP that Visa’s market teams can use to scale reach and impact.

Skills

Required

  • 10+ years of risk experience in banking / consumer lending industry
  • Graduate / Post Graduate degree (Masters or Ph.D.) in Quantitative field such as Statistics, Mathematics, Computer Science, Economics, or equivalent experience
  • Domain expertise in Credit Risk Management
  • Deep understanding of the credit risk industry, key players, regulatory framework and credit risk management best practices
  • Understanding of the credit risk models development approach, decisioning strategy definition and implementation, operational and regulatory reporting
  • Self-motivated, results oriented with strong analytical and problem-solving skills
  • Excellent communication, storytelling and presentation skills
  • Detailed oriented
  • Proven skills in translating analytics output to actionable recommendations
  • Experience in presenting ideas and analysis to stakeholders
  • Expert proficiency in power point and excel
  • Team player with collaborative, diplomatic, and flexible style
  • Strong financial acumen and understanding of profitability drivers of financial institutions

Nice to have

  • Understanding of the consumer Credit risk landscape in AP preferred
  • Ability to tailor data driven results to various audience levels
  • Individual, that upholds and promotes the highest ethical standards and mutual respect in the workplace
  • Exhibit intellectual curiosity and strive to continually learn
  • Proficiency in some of the following statistical techniques: Linear and Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Neural Networks, Clustering, Principal Component Analysis, Factor analysis etc.

What the JD emphasized

  • Credit Risk functional domain
  • risk analytics
  • Credit Risk consulting services
  • issuer portfolio optimization
  • optimization of the client’s processes
  • development of risk models
  • Credit Risk advisory engagements
  • Credit Risk consulting methodologies
  • Credit Risk Management
  • credit risk industry
  • regulatory framework
  • credit risk management best practices
  • credit risk models development approach
  • decisioning strategy definition and implementation
  • operational and regulatory reporting
  • consumer Credit risk landscape
  • analytical and problem-solving skills
  • data driven results