Data and Credit Bureau Attributes Specialist Consumer Credit Risk- Assistant Vice President

Actively Reviewing the Applications

Citi

India, Maharashtra, Mumbai Full-Time On-site

Posted 15 hours ago • Apply by June 15, 2026

Job Description

The Data & Credit Bureau Attributes Specialist (AVP) - Consumer Credit Risk sis responsible for overseeing the end-to-end lifecycle of data utilized in credit risk decisioning systems, rules engines, and regulatory reporting. This role involves leading the integration, governance, and transformation of complex data sets, ensuring the accuracy, consistency, and control of data across multiple platforms and processes. The executive will be responsible for building, testing, and deploying data pipelines that drive mission-critical credit risk decisioning and regulatory compliance efforts.

The ideal candidate will bring expertise in aligning data controls and integration strategies with broader risk management objectives, ensuring data quality supports high-stakes credit decisions, and regulatory reporting is accurate, timely, and compliant.

Key Responsibilities:

Data Governance & Control Framework:

Develop and enforce a governance framework that ensures the accuracy, security, and quality of data throughout its lifecycle—from ingestion to reporting.
Implement data control mechanisms that proactively monitor for and mitigate risks related to data accuracy, completeness, and consistency in credit risk models and decisioning platforms.
Collaborate with senior leadership across Risk, IT, and Compliance to ensure data governance practices align with both internal policies and external regulatory requirements.

Data Transformation & Summarization:

Oversee the transformation of raw and disparate data sets into actionable insights that support both strategic and tactical decision-making within credit risk frameworks.
Lead the implementation of sophisticated data summarization techniques that provide clarity on key performance indicators, risk metrics, and regulatory requirements, ensuring the data drives accurate and timely credit risk reporting.
Drive initiatives that leverage emerging technologies (AI/ML) to enhance the speed, accuracy, and scalability of data integration and summarization processes.

Build, Unit Test, and Deploy Leadership:

Lead the end-to-end delivery process for building, testing, and deploying data pipelines, ensuring seamless integration with rules engines and decisioning platforms.
Oversee the design and execution of unit tests, ensuring that data transformations and controls are thoroughly validated before deployment.
Ensure continuous improvement of data delivery methodologies, promoting automation and operational excellence in the build, test, and deployment of credit risk data solutions.

Regulatory Reporting & Compliance:

Ensure that all data driving regulatory reporting is accurate, timely, and adheres to both internal and external compliance standards, including OCC, CFPB, and Fed regulations.
Collaborate closely with compliance and regulatory teams to ensure that data integration processes meet the evolving demands of regulatory scrutiny and industry best practices.
Provide leadership in designing data-driven processes and systems that streamline reporting, reducing manual interventions while enhancing accuracy and timeliness.

Cross-Functional Collaboration & Stakeholder Engagement:

Engage with senior stakeholders across Risk, IT, Compliance, and Business units to ensure that data strategies are aligned with organizational goals and business outcomes.
Build strong partnerships with technology teams to ensure that data pipelines are seamlessly integrated with credit risk systems, ensuring agility and scalability as business needs evolve.
Act as a key liaison to regulators, industry groups, and external auditors, representing the organization in discussions around data governance, controls, and regulatory reporting practices.

Innovation & Continuous Improvement:

Lead innovation efforts that enhance the automation, scalability, and efficiency of data integration and controls within the credit risk framework.
Stay at the forefront of industry advancements in data governance, AI/ML, and data transformation technologies, applying these insights to continuously improve data management processes.
Proactively identify areas for improvement in the data lifecycle, driving projects that reduce costs, increase accuracy, and improve compliance outcomes.

Key Qualifications:

Educational Background: Bachelor's degree in a relevant field (e.g., finance, risk management, information technology). A Master’s degree or certifications in credit risk, financial analysis is a plus. Certifications in Data Governance, Data Management, or Risk Technology are highly preferred.
Data Governance & Control Expertise:

Extensive experience in designing and implementing data governance frameworks that align with regulatory standards, including experience with data controls, summarization, and transformation in a credit risk context.
Strong expertise in managing data used in decisioning systems, rules engines, and regulatory reporting, ensuring accuracy and consistency throughout the data lifecycle.

Technology & Innovation Leadership:

Demonstrated experience with modern data integration tools, cloud platforms, and emerging AI technologies that drive data transformation, testing, and deployment.
A track record of leading innovation efforts that enhance the automation and efficiency of data delivery, ensuring timely and accurate reporting across credit risk platforms.
Experience in SAS, SAS/Stat, SQL is a must. Any Certifications are an advantage.
Experience working with Digital, Big Data mining tools and technology is an advantage.
Experience working in a large, sophisticated credit granting organization with major credit card, financial services, retail or consulting business a plus.
Experience working with Python & R is a plus.

Stakeholder Management & Executive Communication:

Exceptional communication and presentation skills, with the ability to engage senior leadership, board members, and external stakeholders on complex data and risk management topics.
Proven ability to drive cross-functional collaboration, ensuring that data strategies are aligned with risk, compliance, and business objectives.

Financial Acumen:

Strong financial management skills with experience managing large-scale data projects, including budgeting, forecasting, and cost optimization.

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