Head Data Science

Role Overview: You will be responsible for defining and leading the organizational data science strategy for Commercial Banking in an Indian Banking client. You will lead a dynamic team in a fast-paced environment to drive analytics and data science outcomes across various key areas such as lending, collections, customer analytics, pricing, risk models, and portfolio management. Key Responsibilities: - Own analytics and data science outcomes for Commercial Banking, covering areas like lending, collections, customer analytics, pricing, risk models, and portfolio management. - Define and execute the Commercial Banking analytics strategy aligned with business priorities, regulatory expectations, and enterprise data standards. - Lead a multi-disciplinary team of 20+ members 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 for straight-through processing, automation, and real-time decision support. - Identify, prioritize, and deliver high-impact analytics use cases in collaboration with Commercial Banking leadership. - 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 accountable leader for analytics talent, capability building, vendor partnerships, and external ecosystem engagement within Commercial Banking. - Drive responsible adoption of advanced analytics, machine learning, and AI aligned with data privacy, security, and regulatory requirements. Qualification Required: As 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 in owning large-scale analytics and data science functions with measurable outcomes. - Ability to operate at scale and influence senior business, risk, and technology stakeholders. - Track record of building high-performing analytics teams and delivering sustained business impact. - Proficiency in data fundamentals, with hands-on technical depth preferred. - Exposure to model risk management, regulatory expectations, and governance. Role Overview: You will be responsible for defining and leading the organizational data science strategy for Commercial Banking in an Indian Banking client. You will lead a dynamic team in a fast-paced environment to drive analytics and data science outcomes across various key areas such as lending, collections, customer analytics, pricing, risk models, and portfolio management. Key Responsibilities: - Own analytics and data science outcomes for Commercial Banking, covering areas like lending, collections, customer analytics, pricing, risk models, and portfolio management. - Define and execute the Commercial Banking analytics strategy aligned with business priorities, regulatory expectations, and enterprise data standards. - Lead a multi-disciplinary team of 20+ members 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 for straight-through processing, automation, and real-time decision support. - Identify, prioritize, and deliver high-impact analytics use cases in collaboration with Commercial Banking leadership. - 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 accountable leader for analytics talent, capability building, vendor partnerships, and external ecosystem engagement within Commercial Banking. - Drive responsible adoption of advanced analytics, machine learning, and AI aligned with data privacy, security, and regulatory requirements. Qualification Required: As 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 in owning large-scale analytics and data science functions with measurable outcomes. - Ability to operate at scale and influence senior business, risk, and technology stakeholders. - Track record of building high-performing analytics teams and delivering sustained business impact. - Proficiency in data fun