We’re Hiring Head Data Science | Banking | 18 + Years Exp

The Head Analytics & Data Science is responsible for defining and driving the end-to-end analytics and data science agenda for the Commercial Banking business. This leadership role owns business-critical analytics outcomes across credit, risk, growth, customer engagement, productivity, and portfolio management, ensuring that data-driven decisioning is embedded into core commercial banking processes at scale.Key Responsibilities – * Own analytics and data science outcomes for Commercial Banking across lending, collections, customer analytics, pricing, cross-sell, risk models and portfolio management.

• Define and execute the Commercial Banking analytics strategy aligned to business priorities, regulatory expectations, and enterprise data standards.
• Lead 20+ member multi-disciplinary teams spanning analytics, data science, model development, and advanced analytics use cases.
• Drive development, deployment, and lifecycle management of credit, risk, propensity, and decisioning models, ensuring robustness, explainability, and regulatory compliance.
• Embed analytics into frontline and operational systems to enable straight-through processing, automation, and real-time decision support.
• Partner with Commercial Banking leadership to identify, prioritize, and deliver high-impact analytics use cases with clear business ownership and value realization.
• Work closely with Enterprise Data Platform, Technology, and Architecture teams to ensure comprehensive, scalable, reliable, and compliant data access for analytics.
• Establish strong analytics governance covering model risk management, validation, monitoring, documentation, and audit readiness.
• Act as the single accountable leader for analytics talent, capability building, vendor partnerships, and external ecosystem engagement within Commercial Banking.
• Drive adoption of advanced analytics, machine learning, and AI responsibly, aligned with data privacy, security, and regulatory requirements.

Define organizational data science strategy Lead a dynamic team and work in a fast paced environmentAs a successful candidate, you should have –

• 18+ years of experience across analytics, data science, or quantitative domains, with leadership exposure in banking or financial services.
• Proven experience owning large-scale analytics and data science functions with outcomes
• Ability to operate at scale, influencing senior business, risk, and technology stakeholders.
• Track record of building high-performing analytics teams and delivering sustained business impact.
• Well versed with data fundamentals, hands on and technical depth prefered
• Exposure to model risk management, regulatory expectations, and governance

It is an Indian Banking client

• Work in a fast paced and data driven environment.
• Being responsible for organisation level strategic decision making.