Data Analyst – ML & Credit Risk Analytics

ibex; Karachi Division; On-site; PKR 1,800,000 - 2,400,000; Full time

Job summary

IBEX is seeking a highly analytical Data Analyst in Karachi to support UK-based ML and Credit Risk Analytics teams. You will work with credit card and bureau data, ensuring data quality and enabling predictive modeling and portfolio analysis. Night shifts and UK-regulated data handling are part of the role.

The ideal candidate has strong SQL/Excel skills, experience with large datasets, and familiarity with UK GDPR and data governance. Snowflake experience is a plus for cloud data warehousing.

Qualifications

• Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Economics, or Finance.
• 2–5+ years of experience in data analytics, credit analytics, banking analytics.
• Hands-on experience 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 solid data analysis techniques.
• Experience with Credit Bureau data and familiarity with UK data

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 and potential impacts on model performance.
• Document data sources, business definitions, transformations, assumptions, and validation results.
• Validate metrics, variables, and business rules across ML, credit risk, and analytical workstreams.

Skills

SQL

Excel

Data analysis

Attention to detail

Problem solving

Communication

Education

Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Economics, Finance

Tools

Snowflake

BI tools

Job description

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.