AVP, Evergreen Product Owner

Role Overview

• Engage regularly with model developers, validators, and risk stakeholders to understand their evolving data needs for model development, monitoring, and governance.
• Drive the vision and execution of model operations data products, including curated model datasets, metadata standards, and integration with Model Lifecycle Operations pipelines.
• Partner with analytics, risk, fraud, marketing, and operations functions to identify, define, and prioritize use cases requiring model-ready data.
• Participate in PI Planning sessions and Agile ceremonies to align model operations data features with enterprise goals and cross-functional dependencies.
• Coordinate end-to-end product delivery by working closely with data engineering, information architecture, and cloud platform teams.
• Ensure model operations data assets are compliant with internal data governance, metadata, lineage, and regulatory requirements (e.g., SR 11-7).
• Liaise with Cloud, Data Lake, Data Warehouse, and model governance engineering teams on delivery execution and backlog prioritization.
• Track and report project and program status, deliverables, and value realization across the model operations data portfolio.
• Drive continuous improvement in the availability, explainability, and auditability of curated data assets used in model operations.
• Anticipate, escalate, and resolve cross-team risks, dependencies, and delivery blockers.
• Facilitate alignment with infrastructure, security, and other technical teams when dependencies impact modeling data services.
• Write and prioritize features and user stories with a clear understanding of stakeholder perspectives and business value.
• Regularly refine backlog items to ensure clarity, alignment, and readiness for development.
• Clarify product requirements and ensure delivery meets agreed expectations.
• Oversee UAT in partnership with ML Ops Developers, including writing and/or securing test scripts, maintaining/storing documentation, and obtaining stakeholder sign-offs.
• Lead post-production validation, including writing and/or securing post-prod validation scripts and obtaining sign-off.
• Create and maintain standardized functional documentation for each feature in collaboration with the Data Office.
• Perform other duties and/or special projects as assigned.

Requirements

• Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 7+ years’ experience OR, in lieu of degree, and 9+ years experience with program or product management experience leading complex, cross-functional data or analytics programs.
• 7+ years of experience managing programs or products, including: 5+ years of experience defining business needs, prioritizing data and analytics solutions, and coordinating cross-functional technical execution and 3+ years of experience working in data integration, modeling, warehousing, or big data environments—preferably supporting modeling or advanced analytics.
• Demonstrated experience leading Agile or Scaled Agile programs (SAFe) across cross-functional teams.
• Proven track record of enabling model or analytics platforms, data-as-a-product delivery, or Model Lifecycle Operations/Data Operations functions.
• Agile or Product Owner certification (e.g., CSPO, SAFe PO/PM).
• Broad understanding of credit risk, fraud, marketing analytics, regulatory modeling (e.g., CECL, Basel), or consumer lending data environments.
• Experience working with large-scale data ecosystems, including cloud (AWS, Azure), data lakes, and metadata management tools.

Tech Stack

• AWS
• Azure
• Cloud

Benefits

• Flexibility and Choice for all employees
• Best-in-class employee benefits and programs that cater to work-life integration and overall well-being
• Career advancement and upskilling opportunities