Senior Data Scientist, Ai/ml– Visa Consulting and Analytics

Visa Visa · Fintech · Toronto, Canada, CA

Senior Data Scientist role focused on building and deploying AI/ML solutions for financial services, including predictive models, RAG components, agentic AI systems, and GenAI evaluations. The role involves technical leadership, client engagement, and mentorship.

What you'd actually do

  1. Use and build new predictive models to innovate and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes
  2. Provide technical leadership in a team that generates business insights based on big data, identify impactful recommendations, and communicate the findings to clients
  3. Leverage AI coding tools (e.g., GitHub Copilot, Claude Code, Cline, OpenAI Codex) to accelerate development.
  4. Be an out-of-the-box problem solver who is passionate about applying data science techniques and innovate thinking to our unique data to help our clients both innovate and solve the problems they face
  5. Running projects from scoping to delivery, and engaging with internal/external partners
  6. Develop and deploy ML pipelines, including RAG components, to deliver actionable client insights from transaction data.
  7. Build agentic AI systems with multi-step reasoning, tool use, and memory for complex payment decisioning workflows
  8. Implement GenAI evaluation methods covering quality, bias, and compliance.
  9. Connect with clients to understand the challenges they face and convince them with data
  10. Find opportunities to craft products out of analyses that are suitable for multiple clients
  11. Work with partners throughout the organization to find opportunities demonstrating Visa data to drive business solutions
  12. Synthesize ideas/proposals in writing and engage in productive discussions with external or internal partners
  13. Provide mentorship in modern analytic techniques and business applications, including GenAI best practices, experimentation frameworks
  14. Prioritize and lead multiple data science projects with diverse multi-functional partners

Skills

Required

  • Python
  • SQL
  • Spark
  • Machine learning
  • LLMs
  • GenAI
  • RAG
  • Vector databases
  • Embedding models
  • LLM orchestration frameworks

Nice to have

  • Financial services
  • Credit cards
  • Merchant analytics

What the JD emphasized

  • 4+ years’ experience in data-based decision-making or quantitative analysis, including exposure to LLMs and GenAI applications
  • Experience with LLM orchestration frameworks (LangChain or similar), vector databases, and embedding models
  • GenAI best practices

Other signals

  • Develop and deploy ML pipelines, including RAG components
  • Build agentic AI systems with multi-step reasoning, tool use, and memory
  • Implement GenAI evaluation methods covering quality, bias, and compliance