Chief Operating Officer — Analytics Organisation

The mandate

An analytics organisation in Bengaluru has doubled in three years through business-sponsored teams, acquisitions of specialist capability and rapid lateral hiring. Demand remains strong, but the operating system has not kept pace. Scarce engineers are shared informally, models move into production without consistent support ownership and attrition among experienced managers has widened the gap between promising prototypes and dependable decisions. Business sponsors now receive different answers about capacity, cost and delivery risk.

The new Chief Operating Officer will create coherence across approximately 2,125 employees and material partners and a services perimeter of about ₹3,750 crore. The role covers portfolio intake, workforce and capacity, model operations, service performance, vendor delivery, production readiness and cross-team dependencies. Data scientists and product leaders continue to own analytical quality and roadmaps. The COO owns whether commitments can be delivered repeatedly with the people, controls and support actually available.

This is not a request for a programme office. The appointee must remove low-value demand, establish production disciplines and redesign work where attrition reflects poor jobs rather than a shortage of candidates. The operating model should permit exploration without allowing experiments to inherit critical-service status by accident.

Demand also carries different consequences by use case. A research model can tolerate iteration that would be unacceptable in pricing, workforce allocation or a regulated decision. The COO must create operating tiers that reflect materiality and recovery, then ensure that scarce platform and validation capability is not consumed by low-consequence experiments simply because their sponsor escalates most loudly. Capacity decisions must remain explainable after the immediate pressure passes.

Why this seat is open

Growth made distributed operating responsibility untenable, and the board approved a planned new role before the next capacity cycle. No incumbent is being replaced. A four-to-six-month search allows careful comparison of analytics and service-operations leaders while existing executives retain their accountabilities. The position should be active before the organisation accepts its next major wave of global demand.

What you will own

• Create one demand and capacity view across analytics products, projects, production support and mandatory remediation.
• Define readiness for production, including named service owner, monitoring, support, recovery and user obligations.
• Rebalance scarce engineering and model-operations capability using explicit enterprise priorities rather than sponsor escalation.
• Establish service measures that distinguish analytical development, adoption, run performance and incident recovery.
• Redesign manager spans, shift coverage and specialist roles contributing to avoidable attrition or burnout.
• Govern external partners against delivered capability and production quality, not supplied headcount.
• Lead operational incidents affecting shared analytical services and ensure lessons change design and staffing.
• Build an operating leadership team spanning portfolio, production, workforce, quality and supplier performance.

The first 12 months

In the first 60 days, the COO will reconcile demand, people, vendors and production obligations. By day 90, every critical model service will have an interim owner and support path, the highest-risk capacity collisions will be resolved and new commitments will pass a basic readiness test. The executive committee will receive a baseline of delivery flow, incidents and pivotal attrition.

Months four to nine will establish production-readiness gates, formalise model operations and stop or defer weakly sponsored work. Manager spans and on-call arrangements will change in the most stressed teams. Two priority products should demonstrate shorter transition from validated model to supported use without increased control exceptions.

At year-end, production incidents caused by unclear ownership should fall by 40%, forecast capacity variance should be below 8%, and regretted attrition among pivotal roles should decline by six percentage points. At least 85% of critical analytical services must have tested recovery, while median production transition time improves by 25%.

What the board will measure

• Reliable decision services and transparent escalation when demand exceeds safe capacity.
• Reduction in abandoned prototypes and unsupported production assets.
• Retention and succession across model operations, engineering and portfolio leadership.
• Verified vendor productivity and lower dependence on emergency external capacity.
• Business sponsor confidence grounded in forecast accuracy and delivery acceptance.

The person

You are a COO, analytics-operations head, product-operations executive or senior technology-services leader who has stabilised a rapidly scaled knowledge organisation. You understand model and data lifecycles sufficiently to challenge readiness without usurping analytical ownership. The strongest experience combines workforce recovery, production reliability and demand choices.

You bring 18–22 years of experience and have led at least 1,500 people within a services or technology perimeter of ₹2,150 crore or more. You can show an instance where you refused new work, protected production and subsequently restored capacity. References should distinguish real operating accountability from coordination.

The position is Bengaluru-based and hybrid, with regular attendance during service reviews and incidents.

Compensation and terms

Fixed compensation is expected at ₹3.2–4.6 crore plus performance variable and long-term incentives. Measures will combine service reliability, capacity truth, production flow, pivotal retention and leadership depth. Output volume alone will not define performance. Final calibration reflects current mix and scope, subject to standard vesting and risk conditions.

Confidentiality

The parent, analytical products, business sponsors and capability gaps remain confidential. They will be disclosed to qualified candidates only after mutual interest and an undertaking. The scale and Bengaluru location provide professional context and must not be used to infer a particular employer.