Chief Data and AI Officer

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Signet Jewelers is the world's largest retailer of diamond jewelry, operating more than 2,800 stores worldwide under the iconic brands: Kay Jewelers, Zales, Jared, H.Samuel, Ernest Jones, Peoples, Banter by Piercing Pagoda, Rocksbox, JamesAllen.com and Diamonds Direct. We are a people-first company and this core value is at the heart of everything we do, from empowering our valued team members, to collaborating with our customers, to fostering the communities in which we live and serve. People – and the love their actions inspire – are what drive us. We’re not only proud of the love we inspire outside our walls, we’re especially proud of the diversity, inclusion and equity we’re inspiring inside. There are dynamic career paths awaiting you – rewarding opportunities to impact the lives of others and inspire love. Join us!

The Chief Data & AI Officer (CDAO) is the enterprise-wide executive owner of the company's data assets, applied AI capabilities, and marketing technology ecosystem. This is, first and foremost, a data leadership role: the CDAO is accountable for the strategy, architecture, governance, and value realization of data across the organization and for converting that foundation into business outcomes through applied AI and a modern, activated MarTech stack.
The CDAO leads the transition from fragmented data silos to a unified, product-oriented data operating model, in which a central data organization builds and governs high-quality, discoverable data products on an enterprise platform, in close partnership with business domains. On that foundation, the CDAO builds and scales applied AI (predictive, generative, and agentic) across various business domains including customer data and marketing technology stack that powers personalization, activation, and measurable growth. In doing so, this leader serves as a critical enabler of Signet's Grow Brand Love (GBL) strategy providing the data, AI, and technology foundation that powers brand-led growth, sharper brand distinction, and deeper customer connections across Kay, Zales, Jared, Blue Nile and the broader brand portfolio.

Enterprise Data Strategy & Operating Model (≈40% of role)

• Define and execute the enterprise data strategy, roadmap, and multi-year investment plan, aligned to the Grow Brand Love strategy and corporate growth objectives ensuring data investments directly support brand growth, assortment and pricing decisions, customer experience, and footprint optimization.
• Implement a centrally governed, product-oriented data operating model: data treated as a product (with SLAs, documentation, and named owners), an enterprise self-serve platform, enterprise-wide governance standards, and formal data stewardship roles within business domains.
• Own the enterprise data architecture, including datalake/warehouse platform, ingestion and pipeline frameworks, real-time/streaming capabilities, and the enterprise semantic layer that guarantees one consistent definition of business metrics across all consuming tools and teams.
• Establish and chair the enterprise data governance council; own policies for data quality, metadata, master data management, lineage, retention, privacy, and regulatory compliance (e.g., GDPR, CCPA, and industry-specific regulation).
• Drive data literacy and self-service analytics adoption across the organization
• Own vendor strategy and TCO for the data platforms (e.g., AWS, Databricks, Snowflake, Microsoft Fabric / Azure, dbt, BI tooling), including build-vs-buy decisions and contract negotiation.

2. Applied AI (≈35% of role)

• Define and own the enterprise applied AI strategy and portfolio, prioritizing use cases by business value, feasibility, and risk, spanning predictive ML, generative AI, and agentic automation.
• Build and lead the applied AI/data science organization, including MLOps/LLMOps practices for reliable deployment, monitoring, evaluation, and lifecycle management of models in production.
• Stand up responsible AI governance: model risk management, bias and fairness review, human-in-the-loop standards, security review of AI systems, and compliance with emerging AI regulation.
• Deliver measurable AI outcomes that advance Grow Brand Love priorities across the enterprise (e.g., planning and forecasting, assortment and inventory optimization, pricing and promotion effectiveness, fashion category expansion, customer experience and personalization, marketing optimization, real estate and footprint analytics, service and operations automation) owning the enterprise AI/ML foundation, standards, and tooling that existing modeling teams across the business build upon, and directly providing data science and modeling capacity where dedicated teams do not exist with clear ROI attribution across the portfolio.
• Partner with platform team on the AI platform stack (model hosting, vector/retrieval infrastructure, evaluation tooling) and with HR/Legal on workforce enablement and acceptable-use policy.

3. Marketing Technology & Activation (≈25% of role)

• Own the end-to-end MarTech architecture and engineering: CDP, CRM, marketing automation, tag management, identity resolution, consent management, and experimentation platforms building and operating the stack as the technology owner.
• Develop the MarTech roadmap in close collaboration with the marketing organization, translating marketing-led strategy and business priorities into platform capabilities, integrations, and delivery plans.
• Unify customer data into a governed, privacy-compliant 360° customer view that powers segmentation, journey orchestration, and real-time personalization across channels,  deepening customer relationships and brand love across the brand portfolio and enabling distinct brand experiences for each customer family.
• Lead the technical foundation for first-party data in a post-third-party-cookie environment, including consent, preference management, and clean-room/partner data collaboration where applicable.
• Enable marketing-owned campaign measurement and customer analytics by providing trusted data products, identity resolution, semantic-layer metrics, and analytical tooling with measurement, attribution, and customer analytics execution residing within the marketing organization.
• Rationalize the MarTech portfolio: eliminate redundant tools, drive adoption and utilization of licensed capabilities, and manage total stack spend.

4. Leadership & Transformation

• Build, develop, and retain a high-performing organization across data engineering, data governance, data science/AI, analytics, and marketing technology.
• Serve as the executive voice for data and AI with the C-suite; communicate strategy, progress, risk, and value realization in business terms.
• Drive cross-functional change management: shifting the enterprise from report-requesting to self-serve, data-product-driven decision making.
• Manage the function's budget (capex/opex), vendor relationships, and delivery against committed OKRs.

Why join us:

You’ll have the mandate to build something new: one integrated store experience organization for two distinct, well-loved brands, with the scope to shape how millions of customers experience them

Benefits & Perks

Competitive healthcare, dental & vision insurance

401(k) matching after one year of employment

Generous time off + company holidays

Merchandise discount

Learning & Development programs

Much more!