Bulge Bracket Investment Banks

Posted 11 days ago

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**Data Scientist Director** Lead Bengaluru's Connected Commerce Data & AI CoE. Define, scale AI/ML shared delivery model. Own portfolio, talent, and value realization strategy. Collaborate cross-functionally, deploy, monitor AI/ML solutions. 10+ yrs exp. in data/analytics, proven AI/ML delivery, governance, exec comms.

Compensation: Not specified
City: Bengaluru
Country: India

Full Job Description

Location: Bengaluru, Karnataka, India

Ready to turn AI into real-world impact at enterprise scale? In this role, youll shape how analytics and AI/ML are deliveredbuilding a repeatable model that accelerates high-impact solutions from idea to production. Youll grow your leadership footprint through cross-functional partnership, portfolio ownership, and visibility with senior stakeholders across markets.

Youll join a collaborative, outcome-driven team culture that values disciplined execution, responsible innovation, and shared success.

As an Executive Director, Data and Analytics

within the Connected Commerce Data and AI Center of Excellence

, you will build and scale a shared delivery model that accelerates production analytics and AI/ML capabilities tied to measurable business outcomes. You will own the operating model, talent and capacity strategy, portfolio prioritization, and value realization approach across markets. You will lead end-to-end executionfrom opportunity framing through deployment, monitoring, and adoptionwhile partnering closely with product, technology, and business stakeholders. You will embed governance, model risk readiness, and responsible AI practices into how work gets done so solutions are validation- and audit-ready by design.

Job responsibilities

Define and continuously improve the Data and AI Center of Excellence operating model, including service catalog, delivery standards, reusable assets, and engagement approach

Establish portfolio intake, prioritization, and sequencing with transparent criteria (value, feasibility, risk, time-to-impact, reusability)

Lead end-to-end AI/ML productization, including data readiness, development, validation readiness, deployment into workflows, and ongoing monitoring

Drive adoption by partnering with stakeholders to embed solutions into business processes and decision journeys

Build a benefits realization approach with clear KPIs, measurement methods, and realized value tracking across revenue, cost, risk, and controls

Influence and align matrixed teams across data science, analytics, engineering, product, and run-the-business partners to deliver at pace

Embed governance across the lifecycle, including privacy-by-design, security-by-design, responsible AI practices, and audit-ready documentation

Coordinate run-state ownership for monitoring, change management, and continuous improvement of production AI/ML solutions

Required qualifications, capabilities, and skills

Demonstrated director-level leadership in data and analytics, AI/ML, decision science, or a related discipline within a matrixed enterprise environment

Proven end-to-end delivery of production AI/ML solutions, including deployment, monitoring, and sustained adoption

Demonstrated ability to quantify impact through KPI definition, attribution/measurement approach, and realized outcomes tracking

Proven ability to lead large, multi-disciplinary teams across geographies and influence outcomes without direct authority

Working knowledge of governance and controls relevant to AI/ML delivery (model risk concepts, privacy, security, change control, documentation expectations)

Strong executive communication skills, including the ability to drive alignment and decisions with senior stakeholders

Preferred qualifications, capabilities, and skills

Experience building, scaling, or operating a Data and AI Center of Excellence (or comparable shared delivery model)

Domain exposure adjacent to connected commerce (e.g., digital commerce, payments, customer engagement, marketing decisioning, platform products, operational decisioning)

Experience delivering across multiple markets with differing regulatory and data expectations

Familiarity with production observability and data publishing practices (release management, monitoring, incident response, retraining triggers)

Build and scale a Data and AI Center of Excellence delivering trusted AI/ML products and measurable business outcomes

Full Job Description