Senior Risk Reporting Analyst, Wholesale Credit Risk

Citi

. Lead development and implementation of wholesale credit risk management frameworks .

Posted 9/23/2026full-timeMumbai • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced proficiency in SQL and Python for data management and risk analysis, alongside expertise in regulatory reporting and credit risk frameworks. Capable of designing data models, implementing automated reporting processes, and presenting complex findings to senior stakeholders.

Highest-signal resume keywords

SQL Query OptimizationPython ProgrammingTableau Data VisualizationRegulatory Reporting ManagementMachine Learning Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Credit Risk ManagementData Quality ManagementStatistical AnalysisPropensity ModellingETL Pipeline DevelopmentFeature EngineeringA/B TestingKPI Dashboard DevelopmentAutomated Reporting ProcessesValue at Risk Methodologies

Soft Skills

Stakeholder CommunicationAdvisory SkillsProblem Solving

Tools & Technologies

TableauPower BIGoogle Cloud PlatformVertex AIBigQueryR StudioIBM SPSSJIRAConfluenceMS Visio

Certifications & Qualifications

FRMCFACPA

Industry Keywords

Financial ServicesWholesale Credit RiskRegulatory ComplianceDebt MarketsRisk Governance

Tech Stack

Tools & technologies

BigQueryCloudETLGoogle Cloud PlatformNumpyPandasPythonScikit-LearnSQLTableau

About the role

Key responsibilities & impact

Lead development and implementation of wholesale credit risk management frameworks
Manage the end-to-end regulatory reporting cycle, including FR Y-14 submissions
Evaluate and validate credit risk models, identify gaps, and recommend improvements
Oversee Corrective Action Plan management and track control deficiencies through resolution
Design and implement data models and automated reporting processes
Establish and enforce data quality standards and controls
Contribute to risk governance committees and forums
Advise senior management on risk matters and improve risk controls and operational effectiveness

Requirements

What you’ll need

6 to 10 years of experience in risk management, regulatory reporting, or data management within the financial services industry
Advanced proficiency in SQL, including query optimization
Advanced proficiency in Python, including Pandas, NumPy, and Scikit-learn
Advanced proficiency in Tableau, Power BI, and Advanced Excel, including VLOOKUP and Pivot Tables
Hands-on capability in machine learning, statistical analysis, propensity modelling, A/B testing, and feature engineering
Ability to build and maintain executive scorecards, KPI dashboards, and portfolio analytics
Experience in ETL pipeline development, query optimisation, data quality management, and scheduled job automation
Familiarity with Google Cloud Platform, Vertex AI, BigQuery, R Studio, IBM SPSS, JIRA, Confluence, and MS Visio
Ability to present complex risk findings to senior stakeholders and regulatory bodies
Professional certification such as FRM, CFA, or CPA is beneficial
Working knowledge of sensitivities, Value at Risk, and stress testing methodologies is beneficial
Familiarity with wholesale credit risk systems and platforms is beneficial
Experience in risk management projects in debt markets or wholesale banking is beneficial

Benefits

Comp & perks

Hybrid working pattern with 3 days in the office and 2 days working remotely
Access to structured learning and development programmes
Competitive financial wellbeing benefits, including compensation structures commensurate with seniority and contribution
Wellbeing support and work-life balance initiatives
Access to tools, platforms, and senior relationships needed to make a real impact
Meaningful ownership and cross-functional collaboration
Regular exposure to senior leadership, regulatory engagement, and firm-wide decision-making forums