Key Responsibilities - 

<ul>
<li>Own analytics and data science outcomes for Commercial Banking across lending, collections, customer analytics, pricing, cross-sell, risk models and portfolio management.</li>
</ul>

<ul>
<li>Define and execute the Commercial Banking analytics strategy aligned to business priorities, regulatory expectations, and enterprise data standards.</li>
</ul>

<ul>
<li>Lead 20+ member multi-disciplinary teams spanning analytics, data science, model development, and advanced analytics use cases.</li>
</ul>

<ul>
<li>Drive development, deployment, and lifecycle management of credit, risk, propensity, and decisioning models, ensuring robustness, explainability, and regulatory compliance.</li>
</ul>

<ul>
<li>Embed analytics into frontline and operational systems to enable straight-through processing, automation, and real-time decision support.</li>
</ul>

<ul>
<li>Partner with Commercial Banking leadership to identify, prioritize, and deliver high-impact analytics use cases with clear business ownership and value realization.</li>
</ul>

<ul>
<li>Work closely with Enterprise Data Platform, Technology, and Architecture teams to ensure comprehensive, scalable, reliable, and compliant data access for analytics.</li>
</ul>

<ul>
<li>Establish strong analytics governance covering model risk management, validation, monitoring, documentation, and audit readiness.</li>
</ul>

<ul>
<li>Act as the single accountable leader for analytics talent, capability building, vendor partnerships, and external ecosystem engagement within Commercial Banking.</li>
</ul>

<ul>
<li>Drive adoption of advanced analytics, machine learning, and AI responsibly, aligned with data privacy, security, and regulatory requirements.</li>
</ul>

The Successful Applicant

<ul>
<li>As a successful candidate, you should have </li>
</ul>

<ul>
<li>18+ years of experience across analytics, data science, or quantitative domains, with leadership exposure in banking or financial services.</li>
</ul>

<ul>
<li>Proven experience owning large-scale analytics and data science functions with outcomes</li>
</ul>

<ul>
<li>Ability to operate at scale, influencing senior business, risk, and technology stakeholders.</li>
</ul>

<ul>
<li>Track record of building high-performing analytics teams and delivering sustained business impact.</li>
</ul>

<ul>
<li>Well versed with data fundamentals, hands on and technical depth prefered</li>
</ul>

<ul>
<li>Exposure to model risk management, regulatory expectations, and governance</li>
</ul>

What's on Offer

<ul>
<li>Work in a fast paced and data driven environment.</li>
</ul>

<ul>
<li>Being responsible for organisation level strategic decision making.</li>
</ul>

Data Science

India

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. The Successful Applicant 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 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 What's on Offer Work in a fast paced and data driven environment. Being responsible for organisation level strategic decision making.

Data Science · Mumbai

Job highlights

Skillset required

Job Description

Job Description for Data Science

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