Manager-Fraud Analytics-data Analytics-Banking

Assistant Manager Fraud Analytics | Data Science & Analytics | Hybrid | Banking & Financial Services Role Summary Location-Delhi An 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 Location: Hybrid (2 days office, 3 days work from home)Shift Timing: 11:00 AM 8:00 PMKey Responsibilities 1. Data Collection & Processing Extract, collect, and analyze data from multiple internal and external sourcesPerform data cleaning, transformation, and validation for analytical useEnsure data quality, lineage, governance, and control compliance2. Data Engineering & Automation Design and maintain automated data pipelines for efficient data processingImprove data workflows and support automation initiatives3. Fraud Analytics & Modeling Develop and deploy statistical and machine learning models for fraud detectionIdentify fraud patterns, anomalies, and emerging risk trendsBuild predictive models to forecast fraud risk and business outcomes4. Reporting & Insights Develop dashboards, reports, and analytical insights for stakeholdersTranslate complex data findings into actionable business recommendations5. Stakeholder Collaboration Work closely with risk, business, and operations teamsPresent analytical insights to both technical and non-technical stakeholdersSupport implementation of fraud prevention policies and controls6. Continuous Improvement Enhance analytical frameworks, reporting systems, and automation processesIdentify opportunities where data science can improve risk management and efficiencyRequired Skills & Experience Experience in Fraud Analytics, Risk Analytics, Data Science, or Data Analytics within Banking/Financial ServicesStrong proficiency in SQL and SASExperience working with large datasets and analytical workflowsStrong knowledge of statistical modeling and predictive analyticsUnderstanding of data governance, data quality, and control frameworksStrong communication and stakeholder management skillsAbility to work independently in a dynamic environmentPreferred Skills Advanced SQL and SAS programming expertiseMachine Learning and predictive modeling experienceExposure to fraud detection or financial crime analyticsExperience in building data pipelines and automation frameworksKnowledge of data visualization toolsStrong business acumen and problem-solving skills Assistant Manager Fraud Analytics | Data Science & Analytics | Hybrid | Banking & Financial Services Role Summary Location-Delhi An 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 Location: Hybrid (2 days office, 3 days work from home)Shift Timing: 11:00 AM 8:00 PMKey Responsibilities 1. Data Collection & Processing Extract, collect, and analyze data from multiple internal and external sourcesPerform data cleaning, transformation, and validation for analytical useEnsure data quality, lineage, governance, and control compliance2. Data Engineering & Automation Design and maintain automated data pipelines for efficient data processingImprove data workflows and support automation initiatives3. Fraud Analytics & Modeling Develop and deploy statistical and machine learning models for fraud detectionIdentify fraud patterns, anomalies, and emerging risk trendsBuild predictive models to forecast fraud risk and business outcomes4. Reporting & Insights Develop dashboards, reports, and analytical insights for stakeholdersTranslate complex data findings into actionable business recommendations5. Stakeholder Collaboration Work closely with risk, business, and operations teamsPresent analytical insights to both technical and non-technical stakeholdersSupport implementation of fraud prevention policies and controls6. Continuous Improvement Enhance analytical frameworks, reporting systems, and automation processesIdentify opportunities where data science can improve risk management and efficiencyRequired Skills & Experience Experience in Fraud Analytics, Risk Analytics, Data Science, or Data Analytics within Banking/Financial ServicesStrong proficiency in SQL and SASExperience working with large datasets and analytical workflowsStrong knowledge of statistical modeling and predi