Manager-Fraud Analytics-data Analytics-Banking

July 16, 2026

Assistant Manager – Fraud Analytics | Data Science & Analytics | Hybrid | Banking & Financial ServicesRole SummaryLocation-DelhiAn opportunity for a Data Analytics professional to join the Fraud Analytics function within a global banking and financial services environment. The role focuses on leveraging data science, machine learning, and advanced analytics to detect fraud patterns, enhance risk controls, and support data-driven decision-making. The position involves working with large-scale datasets, predictive modeling, and cross-functional collaboration in a fast-paced, regulated environment.Work Details<ul><li>Location: Hybrid (2 days office, 3 days work from home)</li><li>Shift Timing: 11:00 AM – 8:00 PM</li></ul>Key Responsibilities1. Data Collection & Processing<ul><li>Extract, collect, and analyze data from multiple internal and external sources</li><li>Perform data cleaning, transformation, and validation for analytical use</li><li>Ensure data quality, lineage, governance, and control compliance</li></ul>2. Data Engineering & Automation<ul><li>Design and maintain automated data pipelines for efficient data processing</li><li>Improve data workflows and support automation initiatives</li></ul>3. Fraud Analytics & Modeling<ul><li>Develop and deploy statistical and machine learning models for fraud detection</li><li>Identify fraud patterns, anomalies, and emerging risk trends</li><li>Build predictive models to forecast fraud risk and business outcomes</li></ul>4. Reporting & Insights<ul><li>Develop dashboards, reports, and analytical insights for stakeholders</li><li>Translate complex data findings into actionable business recommendations</li></ul>5. Stakeholder Collaboration<ul><li>Work closely with risk, business, and operations teams</li><li>Present analytical insights to both technical and non-technical stakeholders</li><li>Support implementation of fraud prevention policies and controls</li></ul>6. Continuous Improvement<ul><li>Enhance analytical frameworks, reporting systems, and automation processes</li><li>Identify opportunities where data science can improve risk management and efficiency</li></ul>Required Skills & Experience<ul><li>Experience in Fraud Analytics, Risk Analytics, Data Science, or Data Analytics within Banking/Financial Services</li><li>Strong proficiency in SQL and SAS</li><li>Experience working with large datasets and analytical workflows</li><li>Strong knowledge of statistical modeling and predictive analytics</li><li>Understanding of data governance, data quality, and control frameworks</li><li>Strong communication and stakeholder management skills</li><li>Ability to work independently in a dynamic environment</li></ul>Preferred Skills<ul><li>Advanced SQL and SAS programming expertise</li><li>Machine Learning and predictive modeling experience</li><li>Exposure to fraud detection or financial crime analytics</li><li>Experience in building data pipelines and automation frameworks</li><li>Knowledge of data visualization tools</li><li>Strong business acumen and problem-solving skills</li></ul>