What are the responsibilities and job description for the Technical Product Owner position at Equifax?
What you’ll do
AI Capability Assessment & Business Alignment
AI Capability Assessment & Business Alignment
- Provides inputs to the overall Opportunity Assessment specifically for Gen AI, embedding, and large language model (LLM) product capabilities.
- Identify AI-driven customer needs by partnering with Business Product Managers and internal stakeholders, focusing on opportunities for intelligent automation, content generation, and enhanced search systems.
- Participate in the evaluation of the competitive landscape, market trends, and industry research (e.g., foundation model advancements) to articulate high-potential AI product capability opportunities.
- Conduct market validation, testing Gen AI concepts and prototypes with internal users.
- Provides inputs to the overall Opportunity Assessment specifically for entity resolution, master data management, and data quality platform capabilities.
- Identify foundational data needs by partnering with Data Science, Analytics, Technology, and Business Product teams.
- Participate in the evaluation of vendor solutions and competitive landscapes for data linking, fuzzy matching, and graph database technologies.
- Conduct validation of new data sources and ER methodologies to ensure they meet the quality, privacy, and performance thresholds required by the business.
- Provides inputs in product strategy and planning sessions, specifically outlining the strategic role of the foundational data platform in driving accurate identity and entity-centric data views.
- Understand and communicate the data platform vision, connecting it to the larger strategy for data governance, quality, and enterprise data assets.
- Provides inputs to connect execution KPIs (e.g., entity link rate, match confidence score, data latency) with strategic business goals.
- Define the product backlog for the entity resolution platform, prioritizing features like data ingestion pipelines, standardization rules, matching algorithms, and resolution services.
- Supports the development of business cases for platform enhancements, defining scope, projected ROI (e.g., reduced data errors, increased match accuracy), capacity planning, and resource needs.
- Define and maintain the platform roadmap, ensuring dependencies on infrastructure, data governance, and privacy teams are clearly documented.
- Provides inputs to determine delivery increments that balance architectural robustness with speed-to-market for critical data capabilities.
- Provide technical requirements for platform development, including specifications for data schemas, APIs, data ingestion mechanisms (e.g., streaming/batch), and entity linking logic.
- Articulate and document how specific data requirements connect to the business 'WHY' (e.g., "This new linkage feature is necessary to unify customer records across systems X, Y, and Z").
- Collaborate closely with Data Engineering, Data Architecture, and Datascience teams to identify and document technical trade-offs regarding storage, computation, scale, and performance.
- Work with Legal & Compliance and Data Governance teams to ensure the platform adheres to data residency, privacy, and lineage requirements.
- Collect and process feedback from internal users (Data Scientists, Analysts) to rapidly iterate on platform features and data quality improvements.
- Monitor platform adoption and data usage patterns across various internal teams.
- Track, monitor, and ensure effective performance of the platform, focusing specifically on data quality metrics (completeness, accuracy) and operational costs.