Product Owner – Data Intelligence & AI

Short Summary

Product Owner – Data Intelligence & AI with NielsenIQ. About the Role We are looking for a data-savvy Product Owner to own the horizontal data and AI capability that powers our reference/master data platform across all data domains. Where domain Process Owners own their individual processes, you will own what cuts across all of them: bringing new data sources and markets onto the platform, raising data quality and…

Key Details

• Position / opportunity: Product Owner – Data Intelligence & AI
• Organization: NielsenIQ
• Country / coverage: India
• Location: Chennai, TN, India
• Work arrangement: On-site
• Opportunity type: Jobs
• Sector: Information Technology
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-08-20
• Application deadline: Not specified

Description

About the Role We are looking for a data-savvy Product Owner to own the horizontal data and AI capability that powers our reference/master data platform across all data domains. Where domain Process Owners own their individual processes, you will own what cuts across all of them: bringing new data sources and markets onto the platform, raising data quality and coverage, and embedding AI-driven enrichment, matching, and decisioning into how data is created and maintained. As the Lead, you will set cross-domain data standards and hold cross-stream backlog priority so domain teams stay aligned to a single, coherent data model. This is a hands-on, technical role – fluent in SQL and data validation, comfortable shaping AI use cases from real operational problems, and able to translate them into build-ready user stories and test cases. Key Responsibilities Expand Data Sources & Market Coverage Own the roadmap for onboarding new data sources and feeds, and for expanding market/geographic coverage. Define source-onboarding standards – mapping, quality gates, and reconciliation – so new data lands consistently. Prioritize expansion by value, readiness, and data quality, in partnership with domain Process Owners and Program Managers. Coordinate market/data-source rollout waves – entry criteria, validation, and go/no-go inputs. Own Data Quality & Cross-Domain Standards Define and govern cross-domain data-quality standards, coverage targets, and the shared data model all domains depend on. Build and run data-quality and reconciliation checks (SQL / data validation) across sources and domains. Resolve cross-domain data conflicts and hold priority so domains stay aligned to one coherent data model. Drive AI Integration & Intelligence Shape AI/GenAI use cases from real operational problems – research, enrichment, auto-matching, translation, and coding recommendations. Define confidence-based routing and human-in-the-loop rules so high-confidence outputs flow automatically while low-confidence cases escalate for review. Partner with Data Science and Engineering to validate AI concepts through POCs and pilots, with clear success and continuation criteria. Ensure AI features meet governance, auditability, and operational-quality standards for enterprise deployment. Write Stories, Test Cases & Validate (Technical Core) Translate data and AI needs into build-ready user stories and acceptance criteria . Author and validate test cases for data pipelines, enrichment, and AI outputs – including data-quality, drift, and edge-case scenarios. Verify results directly with SQL and data checks ; own UAT sign-off for data and AI features. Maintain traceability from data/AI need → story → test → release. Across Domains Hold cross-stream backlog priority and align domain Process Owners to shared data and AI standards. Facilitate trade-off decisions across domains, Solution Owners, and Program Managers on release and rollout planning. Provide leadership visibility on coverage, data quality, and AI adoption with clear, measurable outcomes. 8+ years in data product, data/analytics, or data-quality roles, with cross-functional leadership or lead-PO experience. Strong, hands-on SQL and data-validation skills; able to profile, reconcile, and verify data independently at scale. Proven ability to write user stories, acceptance criteria, and test cases , and to run Agile ceremonies. Experience shaping AI/GenAI/automation use cases, including human-in-the-loop workflows, confidence routing, and exception handling. Strong data modelling and systems thinking across sources, process, data, and governance. Excellent stakeholder leadership – able to align multiple Process Owners, Solution Owners, and Program Managers without direct authority. Domain exposure to reference/master data, or large-scale data-quality environments. Experience onboarding new data sources / geographies and running data-migration or convergence validation. Light scripting (e.g., Python) for data checks; familiarity with data-quality frameworks and MLOps concepts. Tools: SQL, Jira, Confluence, Power BI; awareness of orchestration and process-mining tools. Agile / product, data governance, or…

Responsibilities

• About the Role We are looking for a data-savvy Product Owner to own the horizontal data and AI capability that powers our reference/master data platform across all data domains.
• Where domain Process Owners own their individual processes, you will own what cuts across all of them: bringing new data sources and markets onto the platform, raising data quality and coverage, and embedding AI-driven enrichment, matching, and decisioning…
• As the Lead, you will set cross-domain data standards and hold cross-stream backlog priority so domain teams stay aligned to a single, coherent data model.
• This is a hands-on, technical role – fluent in SQL and data validation, comfortable shaping AI use cases from real operational problems, and able to translate them into build-ready user stories and test cases.
• Key Responsibilities Expand Data Sources & Market Coverage Own the roadmap for onboarding new data sources and feeds, and for expanding market/geographic coverage.
• Define source-onboarding standards – mapping, quality gates, and reconciliation – so new data lands consistently.

Requirements / Eligibility

• , reconcile, and verify data independently at scale.
• Proven ability to write user stories, acceptance criteria, and test cases , and to run Agile ceremonies.
• Experience shaping AI/GenAI/automation use cases, including human-in-the-loop workflows, confidence routing, and exception handling.
• Strong data modelling and systems thinking across sources, process, data, and governance.
• Excellent stakeholder leadership – able to align multiple Process Owners, Solution Owners, and Program Managers without direct authority.

How To Apply

Use the Apply now button and follow the instructions on the application page.