Chief Data and AI Officer — Interim, Consumer Goods GCC

The mandate

The board paused a portfolio of generative and predictive AI products after a pricing model used prohibited attributes and claimed benefits could not be reproduced. The data chief left during review, splitting governance from the engineering teams in India.

The interim must assume the global seat within four weeks for eighteen months, taking priority models through remediation and scaled control. Permanent recruitment begins after the council approves the new model-risk standard, with two months reserved for transfer.

Handover requires certified ownership for all production models, eight priority products meeting benefit and risk thresholds for two quarters, critical data elements above ninety-eight per cent quality, and a successor who chairs the council without external support.

The chief may stop models, set data standards, redirect portfolio capacity and approve independent reviews below ₹1 crore. New consumer-data purposes, automation of material pricing decisions and spend above ₹5 crore need council or board approval; business P&L decisions remain with market leaders.

Enterprise ERP replacement, advertising creative and broad cloud sourcing are outside scope. The mandate governs data and models while leaving commercial accountability where it belongs.

Why this seat is open

The pricing incident made the previous decentralised governance model untenable. Executive departure removed the bridge between business sponsors and the India build centre. Temporary global authority is intended to prove an operating system before a permanent chief is selected for the next growth phase.

What you will own

• Inventory every production model by purpose, owner, data, decision consequence, validation and monitoring status.
• Decide which AI products stop, remediate or proceed using documented consumer, regulatory and financial thresholds.
• Establish critical-data ownership with quality rules, lineage and funded remediation obligations.
• Validate benefit through controlled baselines that separate model contribution from pricing, promotion and market effects.
• Institute independent model review, drift monitoring, incident escalation and time-limited risk acceptance.
• Publish portfolio capacity decisions so scarce engineering follows accepted value and risk priorities.
• Transfer the council, model register and eight live product reviews to the permanent chief.

Candidate qualifications

• More than twenty-two years spanning data, analytics and technology, including enterprise chief data or AI accountability.
• Governed production models affecting price, demand, consumer targeting or supply decisions across multiple countries.
• Direct experience stopping or remediating a model for bias, prohibited data, drift or unrepeatable value.
• Deep command of data lineage, quality ownership, model validation, MLOps and accountable human decision design.
• Ability to challenge inflated AI benefits with experimental or counterfactual evidence understandable to finance.
• Proven leadership of large India-based data teams within global product and risk governance.

Non-negotiables

• Can be Bengaluru-based within four weeks and attend global governance regularly.
• No investment or advisory role with AI vendors considered by the organisation.
• Prepared to stop high-profile models when decision or data risk exceeds tolerance.
• Available exclusively for the eighteen-month build and successor transition.

1. 49 words maximum. Confirm availability and disclose any current AI vendor, board or advisory commitments.
2. 49 words maximum. Which production model did you stop, and what observed harm or control failure drove the action?
3. 49 words maximum. How did you prove an AI benefit independently of concurrent commercial changes?