Chief Data Officer — Digital Marketplace

The mandate

The marketplace holds large volumes of seller, catalogue, transaction, fulfilment, return and complaint information, but trust decisions still rely on fragmented evidence. The same seller may operate through related entities, materially similar products can appear under different descriptions, and customer complaints are classified for service rather than risk detection. Analytical models identify suspicious behaviour, yet their inputs and false-positive effects are not consistently understood by the executives who decide whether to restrict a seller or item.

The Chief Data Officer will build the information and analytical system behind a marketplace trust intervention. The remit covers data strategy, governance, seller and product information, entity resolution, trust data products, analytical engineering, model governance, quality, lineage and responsible use. Marketplace and risk leaders own enforcement decisions; product-safety and legal functions retain their authority; technology operates the infrastructure. The CDO is accountable for evidence that is timely, traceable and fit for the consequence of the decision.

This planned replacement requires a shift from central data accumulation to decision products. The board does not want success measured in petabytes, dashboards or model counts. It wants earlier detection, fewer avoidable false restrictions and a clearer account of why an intervention occurred. The CDO must also know when available data cannot support the requested conclusion.

Scope and operating context

Based onsite in London, the role influences approximately 900 employees and material partners across the United Kingdom and a wider international region. Direct and matrix teams include data governance, analytical engineering, data science, entity-resolution specialists, model risk, data-product management and regional analytics. Domain experts in marketplace, customer care, payments, fulfilment and product quality will remain responsible for meaning and action.

Seller identity is difficult by design and circumstance. Legitimate groups may use several entities or storefronts across markets, while abusive operators may attempt to re-enter after restriction. Product identity is equally complex across barcodes, seller-created listings, bundles, variants and cross-border records. The CDO will create confidence-based relationships with provenance and review, rather than present uncertain matches as facts.

Trust data is sensitive. Seller financial and identity records, customer complaints, images, payment signals and investigation outcomes have strict purpose and access requirements. Combining them can improve protection but can also create unfair inference. Data use must be lawful, proportionate and monitored, with qualified human judgement for consequential decisions.

First-year agenda

The first one hundred days will trace several material trust decisions from initial signal through evidence, action and appeal. The CDO will identify which sources arrived late, where definitions changed, how manual labels were created and whether downstream learning returned to the data system. Model performance will be segmented by category, seller type and market rather than judged through a portfolio average.

The executive will then define authoritative trust domains. Seller, product, listing, transaction, shipment, return, complaint and intervention records will have accountable business owners, quality expectations, lineage and retention. Shared identifiers and event timing should allow a risk team to see sequence and relationship without overwriting legitimate commercial hierarchies.

Several decision products will be prioritised. One may connect complaint language, returns and seller relationships to identify emerging product concern; another may show the complete evidence and confidence behind a related-seller assessment; a third may measure whether restrictions prevent harm or simply move it to a new listing. Each product needs an executive user, action path and measurable adoption.

Model governance will be strengthened for seller scoring, product risk, fraud and content moderation. Teams must document target, features, training data, drift, segment performance, override and appeal. Models using proxies with material fairness or legal risk will be challenged. The CDO will ensure investigators can understand the main evidence without exposing methods in ways that enable evasion.

Customer-care information will be redesigned for dual use: immediate remedy and pattern detection. Taxonomy should be simple enough for service colleagues, while text and image analysis can support specialist review within approved boundaries. Feedback from confirmed cases must improve classification. By year-end, priority trust decisions should have clearer lineage and materially better detection-to-action time.

Leadership responsibilities

The CDO will chair data priority and model-governance forums, while domain leaders remain accountable for information meaning and enforcement use. The central team will provide engineering, standards, discoverability and independent challenge. Persistent quality failure must be addressed at the source process, not through endless analyst correction.

The executive will build a team that values explanation and operational adoption. Data scientists and engineers should work alongside seller investigators, customer-care colleagues and product specialists. Vendor tools will be assessed for portability, auditability and performance in the platform's actual categories, not accepted on aggregate benchmark claims.

Board reporting must separate fact, inferred relationship, model score and executive judgement. The CDO will state evidence confidence and false-positive risk and will resist pressure to claim certainty for a visible incident. When a model fails, learning and affected-decision review will be as important as technical correction.

Measures of success

The board will monitor signal-to-action time, confirmed precision and recall where measurable, false restrictions, appeal outcomes, re-entry detection, repeat product issues, lineage coverage and data-quality resolution. Measures will be segmented by category and seller population. Harm prevented will be estimated conservatively with assumptions disclosed.

Data-product success will include adoption in trust workflows, reduced manual evidence gathering, faster case preparation, reliable freshness and lower duplicated analysis. Model progress will include documented ownership, monitoring, drift response and retirement when no longer fit. Dashboard usage without a changed decision will not count as value.

Candidate profile

Candidates should bring 18–22 years across enterprise data, analytics and model governance in marketplaces, payments, retail, platforms, safety or another high-volume decision environment. They must have led production data products used in consequential seller, customer or transaction decisions across countries.

The board will seek examples of resolving seller or entity relationships under uncertainty, improving detection through complaint or product data and changing a model after segment-level false positives emerged. Candidates should understand lineage, label quality, feedback loops, privacy and appeal at a practical level.

The successful CDO will combine technical authority with humility about inference. They must challenge risk leaders who want a definitive answer unsupported by data and data scientists who value model performance above human consequence. Clear communication with boards and operational teams is essential.

Compensation and appointment terms

The indicative annual base is GBP 250,000–340,000, supplemented by annual incentive and long-term participation linked to trust and enterprise outcomes. Final positioning will reflect relevant decision scale, model-governance depth and current arrangements. Mobility support or responsible treatment of forfeited awards will be assessed during final discussions.

Confidentiality

The marketplace is unnamed because the search involves detection methods, seller information and active interventions. Detailed data, model and governance information will be disclosed gradually after identity, conflict and confidentiality checks. Applications must exclude seller identities, investigation data, customer records, proprietary features and security details from other organisations.