Director, Commercial Data Strategy

Mondelēz International•East Hanover, NJ

2d•$142,700 - $235,455•Remote

About The Position

Mondelēz International is looking for a Director, Commercial Data Strategy to own and advance the company's commercial data agenda across Sales, Insights & Analytics (I&A), Customer Experience (CX), and adjacent functions. This role is the connective tissue between our commercial data assets, our vendor ecosystem, and the teams that turn data into growth — ensuring we have the right data, from the right sources, governed and activated the right way. The ideal candidate brings deep fluency in syndicated and panel data (including Nielsen/NielsenIQ), but pairs it with a broader, more modern perspective on the full commercial data landscape — retail media data, brand tracking data, shopper/loyalty data, e-commerce signals, and emerging alternative data sets. They see beyond any single vendor and can architect a fit-for-purpose data strategy that reflects how commercial decisions are actually made today.

Requirements

10+ years in data strategy, data management, commercial analytics, or a related field within CPG, FMCG, or a similarly data-intensive industry.
Deep Nielsen/NielsenIQ expertise — understands the data, the contracts, the methodologies, and the limitations — combined with hands-on experience across other major commercial data providers (Circana/IRI, Kantar, retailer data, etc.).
Proven track record of building and executing enterprise-level data strategies across multiple functions and geographies.
Strong experience in vendor/contract management for commercial data assets.
Demonstrated ability to deploy AI/ML capabilities on commercial data — ideally including piloting in test markets and scaling successful approaches.
Experience supporting or operating in global organizations with varying levels of regional data maturity.
Bachelor's degree required

Nice To Haves

Advanced degree (MBA, MS in Analytics, Data Science, or related field) preferred.

Responsibilities

Define and maintain a multi-year commercial data strategy aligned to Sales, I&A, CX, and broader enterprise priorities.
Evaluate the commercial data ecosystem end-to-end — syndicated data (Nielsen, Circana, etc.), retailer/shopper data, brand tracking data, and emerging sources — and recommend the optimal portfolio of data assets.
Identify gaps, redundancies, and opportunities across the current data landscape; build a clear roadmap to close them.
Serve as the internal authority on commercial data — what we have, what we need, and how it connects.
Partner with the Digital Services function to build AI-ready data and technology platforms.
Own the commercial data vendor relationship lifecycle: sourcing, negotiation, contracting, RFPs, renewals, and performance management.
Manage contracts and commercial terms for key data providers (e.g., NielsenIQ, Circana/IRI, Kantar, retailer data partnerships) to maximize value and minimize risk.
Establish and enforce vendor SLAs, data quality standards, and escalation protocols.
Act as the central point of accountability for vendor-related issues, including in local/regional markets where data operations are less mature.
Serve on the data governance enterprise council, acting as the owner of the key market data domain
Provide hands-on support to regional and local teams when vendor or data issues arise — particularly in markets with less-developed data infrastructure.
Troubleshoot data delivery, quality, and access issues in partnership with local I&A and Sales teams.
Build lightweight, scalable playbooks so that regional teams can resolve common issues independently over time.
Champion the integration of AI and machine learning into commercial data workflows — from data harmonization and quality automation to predictive analytics and insight generation.
Identify and build out AI capabilities in select test markets, proving value before scaling.
Partner with IT and champion the integration of AI-driven solutions into everyday commercial data processes.
Stay current on AI/ML innovations relevant to commercial data (e.g., LLM-based data cataloguing, automated anomaly detection, NLP-driven insight extraction) and assess applicability.
Work across Sales, I&A, CX, Marketing, Finance, and Supply Chain to ensure commercial data strategy serves the full breadth of business needs.
Translate complex data topics into clear, actionable language for non-technical stakeholders.
Influence without authority — build alignment across functions and geographies on data standards, priorities, and investments.