Product Manager – Panel Data & Analytics Platforms

NielsenIQ•Chicago, IL

11h•Remote

About The Position

NIQ operates one of the largest and most trusted consumer panel datasets in the world. As our data offerings evolve, we are investing in new ways to deliver deep, flexible, and secure access to panel data—including analytics-ready extracts, governed data environments, and standardized analytical tools. We are looking for a Product Lead to help turn these strategies into reality. This role focuses on execution and enablement across NIQ’s panel data platforms, including advanced data extracts, analytics use cases, and evolving delivery models. You will work closely with data science, engineering, sales, operations, and other product leaders to help define, launch, and scale new ways customers access and analyze NIQ panel data. You do not need prior product management experience or deep engineering skills. This role is ideal for someone with a strong analytics, data, or client-facing background who wants to grow into full product ownership over time. This role spans multiple panel data initiatives, including (but not limited to): Analytics-ready panel data extracts, Governed and secure data delivery models, Standardized analytics and modeling use cases built on panel data, Commercial packaging and operational processes for data products. You will be responsible for helping ensure these offerings are clearly defined, operationally sound, and commercially usable.

Requirements

2–6 years of experience in analytics, data science, insights, technical customer success, consulting, operations, or similar roles.
Experience working with complex datasets or analytical workflows.
Strong analytical reasoning and ability to understand how data is structured and used.
Comfort working with ambiguity and loosely defined problems.
Ability to collaborate across highly technical and commercial teams.
Clear communicator who can explain complex ideas simply.
Curious, motivated, and eager to grow into a broader product role.
Comfortable taking ownership without needing formal authority.
Willing to challenge assumptions thoughtfully and bring new ideas forward.
Execution-oriented: you enjoy turning ideas into things that actually ship.

Nice To Haves

Experience in consumer data, FMCG, retail, or analytics platforms.
Exposure to data platforms, analytics products, or data governance concepts.
Prior experience supporting enterprise clients or internal sales teams.
Familiarity with SQL, BI tools, or large-scale data environments (no coding required).

Responsibilities

Help translate product strategies into concrete deliverables, timelines, and processes.
Support the build-out of scalable analytics and data-access capabilities.
Identify where bespoke work can be standardized or productized.
Partner closely with data science and engineering teams to shape how data, models, and workflows are implemented.
Collaborate with sales and client teams to ensure offerings are understandable, sellable, and repeatable.
Coordinate with operations, legal, and other product leaders to align on delivery models, constraints, and guardrails.
Help define how panel data products are packaged, positioned, and rolled out to customers.
Support early implementations to validate assumptions and surface improvements.
Create internal documentation, playbooks, and process clarity for go-to-market teams.
Own intake and prioritization of requests related to panel data products.
Surface tradeoffs, risks, and decisions and bring them to leadership with clear options.
Push back constructively when scope or approach could create long-term issues.
Ensure analytics-ready panel data extracts are clearly defined, operationally sound, and commercially usable.
Ensure governed and secure data delivery models are clearly defined, operationally sound, and commercially usable.
Ensure standardized analytics and modeling use cases built on panel data are clearly defined, operationally sound, and commercially usable.
Ensure commercial packaging and operational processes for data products are clearly defined, operationally sound, and commercially usable.