AVP, AI Modeling Platform - L11

• Own the vision, strategy, and multi-quarter roadmap for agentic AI solutions that improve bank decisioning outcomes (e.g., fraud/financial crime, credit decisioning, marketing next-best-action, collections, servicing).
• Lead the AI Modeling Platform (AMP) as a product by defining capabilities, prioritizing features, and ensuring reusable components (decision agents, tool use, orchestration, evaluation, monitoring) that accelerate delivery across lines of business.
• Translate business problems into measurable value cases (loss reduction, approval rate lift, fraud capture, cost-to-serve reduction, customer conversion lift) and track benefits realization.
• Establish standards for agent safety, governance, and controls appropriate for regulated banking use (human-in-the-loop, auditability, model/agent documentation, monitoring and escalation playbooks).
• Lead and grow a team of data scientists / ML engineers / decision scientists building agentic solutions end-to-end (prototype → production).
• Coach team members in agentic AI patterns (planning, tool-use, RAG, workflow orchestration, multi-agent collaboration), and in bank decision science fundamentals (risk, uplift modeling, scorecards, optimization, experimentation).
• Build a sustainable talent pipeline through hiring, onboarding, career development, and performance management; create an inclusive culture of high standards, continuous learning, and operational excellence.
• Drive end-to-end Agile delivery from discovery through scaling and lifecycle management, ensuring production-grade performance (reliability, latency, cost, security/privacy, resiliency, monitoring) and rigorous agent evaluation controls (test suites, red-teaming, guardrails, bias/fairness, drift, incident response).
• Drive enterprise partnership and scale by aligning cross-functional stakeholders (Fraud/FC, Credit Risk, Marketing, Collections/Servicing, Data/Engineering, Model Risk, Compliance/Legal, InfoSec, Ops) and cross-region teams (US/IAH) around the platform value proposition to enable adoption and reuse at scale.
• Stay ahead of agentic AI/LLMOps and regulatory/MRM trends and use that expertise to consult with stakeholders to identify high-impact decision opportunities, co-design solutions, align success metrics, secure resources, and convert best practices into actionable standards for AMP and delivery teams.

Required Skills/Knowledge:

• Bachelor’s or master’s degree in Statistics, Economics, Mathematics, or a related quantitative discipline, with 7+ years of hands-on analytics experience or 9+ years of relevant experience in lieu of a degree.
• Experience building and operationalizing agentic AI on AWS (AgentCore/Bedrock), including secure tool/data access, guardrails, and monitoring/evaluation.
• Proficiency with LangChain/LangGraph for RAG and agent orchestration (multi-step workflows, retries, human-in-the-loop).
• 7+ years of hands-on analytics experience using tools such as SQL, SAS, Python, Spark, Scala, and Hive, with demonstrated ability to apply advanced analytical techniques and efficiently work with complex, large-scale datasets.
• Proven experience managing a diverse, cross-functional team of analysts, data scientists, and data engineers across multiple technologies, including SQL, SAS, Python, D3.js/charting libraries, JavaScript, Java, Node.js, HTML, Spark, Scala, Hive, and MySQL.
• 4+ years of team and project management experience, with the ability to define and continuously improve best-in-class delivery models and adapt approaches quickly in an agile environment.
• Strong working knowledge of Agile methodologies (e.g., Scrum, Kanban) and proficiency with Atlassian tools such as JIRA and Confluence.
• Demonstrated ability to resolve complex technical and people-related challenges with minimal supervision.
  • Ability to balance effective team leadership with hands-on contribution to critical project delivery.