Data Analyst - ML & Credit Risk Analytics

ibex · Karachi, Karachi District; Sindh, Pakistan

IBEX is hiring a highly analytical and detail-oriented Data Analyst on behalf of its client to support the client’s Machine Learning and Credit Risk Analytics teams in developing, validating, and monitoring predictive models and portfolio analytics . The role will focus on preparing and analyzing credit card and credit bureau data to support forecasting, delinquency prediction, customer behavior analysis, credit risk assessment , and ongoing model performance monitoring .

The ideal candidate will have strong SQL and Excel capabilities, hands-on experience with large and complex datasets , direct experience working within UK-based teams or on UK data/portfolios , applied experience with AI/ML-driven analytics workflows , and a solid understanding of UK data protection regulation . Experience with Snowflake and credit bureau data will be highly valuable. This role operates on a night shift schedule .

Key Responsibilities:

• Prepare, extract, transform, and validate datasets required for machine learning model development, validation, and monitoring .
• Support Data Scientists and ML teams with historical and current datasets for forecasting, delinquency prediction, customer behavior, and credit risk models .
• Perform data profiling, reconciliation, quality checks, and anomaly detection before data is used in analytical or ML workflows.
• Investigate data issues and perform ad-hoc analysis and deep dives to identify trends, anomalies, and potential impacts on model performance.
• Support feature and variable analysis by assessing data completeness, consistency, stability, and business relevance.
• Document data sources, business definitions, transformations, assumptions, and validation results to support repeatable analytical processes.
• Apply hands-on experience with AI/ML-driven analytics or model-support workflows to evaluate and improve the usability of data for predictive modeling .
• Analyze credit card portfolio metrics including balances, payments, utilization, delinquency, charge-offs, recoveries, and customer behavior.
• Work with Credit Bureau data and understand key bureau attributes used in credit risk assessment and customer segmentation .
• Analyze credit scores, payment history, utilization, account history, inquiries , and other relevant bureau characteristics.
• Identify trends and data patterns that may influence credit risk, customer behavior, portfolio performance, and model outcomes .
• Support the ML team in evaluating relationships between customer characteristics, credit behavior, and delinquency or loss outcomes .
• Assist with portfolio segmentation, performance monitoring , and analysis of emerging credit risk trends .
• Perform validation and reconciliation across internal systems, Credit Bureau data , and other external data sources.
• Identify missing, duplicate, inconsistent, inaccurate, or anomalous records that could affect analytical or model results.
• Investigate data discrepancies, determine root causes , and work with relevant teams to resolve data quality issues .
• Validate key metrics, variables, and business rules used across ML, credit risk, and analytical workstreams .
• Develop and maintain repeatable data quality checks and validation processes .

4. UK Data Regulations & Data Governance:

• Ensure data handling and analytical activities follow applicable UK GDPR and Data Protection Act 2018 requirements.
• Apply data minimization, purpose limitation, and appropriate data protection principles when working with customer and Credit Bureau data.
• Ensure appropriate handling and protection of Personally Identifiable Information (PII) and sensitive customer information.
• Follow approved data access, retention, sharing, and disposal policies .
• Support data governance, audit requirements, documentation, and controls related to ML and analytics activities.
• Maintain working knowledge of relevant UK data protection and financial services regulatory requirements , gained through direct application in a UK-regulated environment .

Required Qualifications & Experience:

• Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Economics, Finance , or a related field.
• 2–5+ years of experience in data analytics, credit analytics, banking analytics , or a related field.
• Hands-on experience working with credit cards, consumer lending, banking, or financial services data .
• Strong SQL skills for querying, transforming, manipulating, and validating large datasets .
• Strong Excel skills and a solid understanding of data analysis techniques .
• Experience working with Credit Bureau data and credit-related customer attributes.
• Experience working with large datasets and performing data quality, validation, and reconciliation checks .
• Experience with Snowflake or another cloud data warehouse is preferred.
• Direct professional experience working within a UK-based team, UK employer, or on UK customer/portfolio data .
• Working knowledge of UK GDPR and the Data Protection Act 2018 , with demonstrable application in a professional setting.
• Applied experience working with or directly supporting AI/Machine Learning workflows, model development, or model monitoring .
• Ability to communicate analytical findings clearly to both technical and non-technical stakeholders.
• Strong analytical thinking, attention to detail, ownership, and problem-solving skills .
• Must be willing and able to work night shift hours to align with UK business hours.

Preferred Qualifications:

• Experience supporting Machine Learning, Data Science, Predictive Analytics, or Credit Risk teams .
• Experience working with UK consumer credit card portfolios .
• Strong understanding of Credit Bureau data and its application in credit risk modeling .
• Formal training or certification in UK GDPR, Data Protection Act 2018, or data governance practices .
• Experience with portfolio performance, delinquency, charge-off, loss, and recovery analytics .
• Experience working in fast-paced, data-driven financial services environments .
• Familiarity with data visualization or BI tools is a plus.

Reporting Cadence & Performance Expectations:

• Provide timely, accurate, and well-validated datasets to support ML model development and monitoring .
• Deliver recurring portfolio, data quality, and analytical reports within agreed timelines.
• Proactively identify and communicate data issues that may impact model development, portfolio reporting, or analytical conclusions.
• Support rapid-response analytics and ad-hoc deep dives for emerging business, portfolio, and credit risk questions.
• Maintain clear documentation of analytical methodologies, data sources, assumptions, and validation outcomes .
• Ensure all customer and Credit Bureau data is handled securely and in accordance with applicable UK regulatory requirements .