Director, Data & Insights Products

Condé Nast is one of the world's most renowned media publishing companies, creating and distributing every type of media today, spanning print and digital publishing in all formats. With a portfolio of some of today's most influential brands, the company continues to grow its audience through a global operational and content infrastructure across its 12 owned and operated markets. Headquartered in New York City, the company's owned and operated markets include China, France, Germany, India, Italy, Japan, Mexico & Latin America, Spain, Taiwan, UAE/Dubai, the U.K., and the U.S., with additional local license partners in over twenty additional markets across the globe. Lead brands include Vogue, The New Yorker, GQ, Architectural Digest, Condé Nast Traveler, Vanity Fair, Wired, Allure, Ars Technica, Bon Appétit, House & Garden, Pitchfork, Tatler, and Vogue Business.

Job Description

Location:
New York, NY

Condé Nast is seeking a Director of Data & Insights Products to join our Data Product function and transform how our brands, Analytics teams, Product teams, Editorial teams, and business leaders access, understand, and use data. This leader will define and deliver the product strategy for the enterprise data consumption and enablement experience: the trusted data products, semantic and context layers, AI interfaces, business-intelligence capabilities, and operating practices that turn complex data into confident decisions.

This is a highly visible, stakeholder-centered role. The Director will work deeply with users across Condé Nast’s brands and global functions to understand how decisions are made today and how data and AI can be embedded into everyday workflows. They will partner with Data Engineering, Analytics, Editorial, Content Operations, Revenue, Governance, Product, and Legal teams to make trusted, business-ready data discoverable and usable at scale.

A successful candidate will be as comfortable facilitating a difficult KPI-definition discussion with senior stakeholders as they are shaping a semantic layer for conversational analytics, evaluating BI experiences, or working with engineers on data contracts and quality standards. They will bring strong product judgment, organizational influence, and a practical point of view on how data can scale business decisions and AI practices at Condé Nast.

What You’ll Do

Set the platform and enablement strategy

- Own the vision, strategy, and roadmap for Condé Nast’s data platform and insights-enablement product portfolio, spanning trusted curated data, semantic and metrics layers, data discovery, BI, conversational analytics, and AI-powered data experiences.
- Define a coherent user experience for accessing data across tools and surfaces so employees do not need to understand the underlying technical landscape to find a reliable answer.
- Establish clear product principles for self-service, governed access, build-versus-buy decisions, platform reuse, and the appropriate role of dashboards, alerts, assistants, and workflow-integrated insights.

Advance AI-powered data products and experiences

- Define the product strategy for using enterprise data to power AI-enabled analytics and decision-support experiences, helping users explore business questions, understand performance drivers, and move more quickly from insight to action.

- Partner with Product, Engineering, Analytics, and Governance to establish the semantic, metadata, lineage, and contextual-knowledge foundations required for accurate, explainable, and trusted AI outputs.
- Lead product discovery and adoption for AI capabilities, including use-case selection, experience design, evaluation standards, guardrails, feedback loops, and integration into existing business workflows.
- Continuously assess the evolving AI and analytics landscape and recommend where Condé Nast should build, buy, partner, consolidate, or retire capabilities.

Build trust into our data

- Make user trust a primary product outcome. Establish a clear framework for certified data products and metrics, including definitions, ownership, lineage, freshness, quality expectations, limitations, and visible status communication.
- Partner with Analytics and Data Engineering to resolve competing KPI definitions and ensure that approved metrics are implemented consistently in business-ready data products.
- Define expectations for data contracts, testing, observability, incident response, and user communication so that quality issues are detected, explained, and resolved transparently.
- Create mechanisms for users to challenge, correct, and improve data and AI-generated answers, and use recurring trust issues to inform roadmap priorities.

Lead through stakeholders and user outcomes

- Build trusted relationships with senior leaders and practitioners across Editorial, Content Operations, Revenue, Audience Development, Product, Finance, and Analytics, as well as Condé Nast’s brands and global markets.
- Conduct ongoing discovery to understand user personas, decisions, workflows, pain points, and unmet needs; convert those findings into scalable platform capabilities rather than one-off solutions.
- Create cross-functional forums that align business owners, Analytics, Product, Governance, and Engineering on priorities, definitions, trade-offs, and adoption plans.
- Communicate strategy, roadmap, progress, risks, and value clearly to executive stakeholders while maintaining enough technical depth to guide delivery teams.
- Serve as the connective tissue between users and technical teams, ensuring that Engineering can focus on durable platform development while stakeholders have clear Product ownership and accountability.

Drive adoption, enablement, and measurable value

- Own the full product lifecycle from discovery and definition through launch, enablement, adoption, measurement, and continuous improvement.
- Develop product marketing, training, documentation, office hours, champion networks, and change-management approaches that meet users in their existing workflows.
- Define and monitor portfolio OKRs and product-health measures, including trust, adoption, task completion, time-to-insight, self-service, support burden, data quality, and business impact.
- Use adoption data, qualitative feedback, and experimentation to determine which capabilities to scale, redirect, consolidate, or discontinue.
- Identify high-value brand or functional use cases that can demonstrate impact quickly while creating reusable enterprise capabilities.

Build a strong product operating model

- Establish clear intake, prioritization, roadmap, and release practices for the portfolio, balancing strategic platform investments with urgent business needs.
- Lead cross-functional squads, providing strategic direction, mentorship, and coaching to Product team members who partner across the organization to build and evolve data product capabilities
- Partner closely with global Engineering, Analytics teams, and other stakeholders to create clear accountability, productive ways of working, and strong connections between US stakeholders and delivery teams.
- Foster a culture of curiosity, accountability, experimentation, and continuous learning, encouraging teams to challenge assumptions, proactively identify opportunities, and take initiative without waiting for fully defined direction.

How you will lead

- Stay close to users, using their feedback and evidence to shape priorities and challenge assumptions.
- Take ownership through delivery, adoption and measurable value, making clear decisions and addressing problems transparently.
- Bring curiosity and initiative, turning emerging opportunities into practical experiments and action.
- Move quickly and maintain focus, simplifying decisions and dependencies without compromising quality or trust.
- Use AI as a default part of your own work and help teams rethink how they discover, build and support data products.
- Reach beyond your formal remit to solve important problems, respecting expertise and keeping accountability clear.

The Ideal Candidate

- 8+ years of product management experience, including data platforms, analytics, business intelligence, AI-enabled products, or enterprise software
- Deep understanding of modern data-platform concepts, including lakehouse or warehouse architectures, curated data layers, data contracts, observability, lineage, metadata, governance, and role-based access.
- A track record of defining strategy and delivering enterprise data or analytics products from discovery through adoption and measurable impact—not only technical implementation.
- Exceptional stakeholder-management and communication skills, with the ability to build trust, navigate competing priorities, and influence senior leaders across business, editorial, analytics, product, and technology functions.
- Strong product discovery and change-leadership skills; demonstrated ability to understand varied user workflows and drive adoption across a complex organization.
- Practical experience with AI-enabled analytics, conversational BI, semantic layers, metrics layers, knowledge or context systems, and the evaluation and governance of AI-generated outputs.
- Strong analytical judgment and the ability to determine when a metric, model, or AI-generated answer does not reflect business reality.
- Experience partnering closely with Data Engineering, Analytics, Revenue, Legal and other stakeholder teams; able to translate technical complexity into clear user and business value.
- Experience defining product OKRs and using adoption, quality, efficiency, and business-impact measures to make portfolio decisions.
- A hands-on product leader who combines strategic thinking with the willingness to enter the details when needed.
- A listener and translator who earns credibility with both business users and technical teams.
- A systems thinker who can connect individual requests to reusable platform capabilities.
- Media, publishing, subscription, advertising, or digital consumer-product experience is helpful but not required.

The expected base salary range for this position is from $195,000-220,000. Salary offers are based on a wide range of factors including but not limited to relevant skills, training, experience, and education.

What happens next?

If you are interested in this opportunity, please apply below, and we will review your application as soon as possible. You can update your resume or upload a cover letter at any time by accessing your candidate profile.

Condé Nast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status and other legally protected characteristics.