Senior Manager – Analytics, AI Driven Strategy

Role Overview

• Lead advanced analytics using SQL, SAS, Python, and AI/Gen AI techniques to detect emerging fraud patterns.
• Conduct in depth evaluations of VRM/FraudGuard rules; recommend enhancements to improve detection accuracy and reduce false positives.
• Develop analytical models, scenario analyses, and predictive approaches to strengthen fraud surveillance.
• Champion the integration of AI/Gen AI tools in fraud detection workflows.
• Oversee productivity, SLA adherence, and performance analytics of fraud detection teams across Issuing and Acquiring.
• Conduct root cause and gap analysis to highlight inefficiencies and recommend actionable improvements.
• Develop performance dashboards and scorecards using Power BI and Excel.
• Ensure timely, accurate, and automated MIS for senior leadership, committees, regulators, and other stakeholders.
• Deliver comprehensive, data driven presentations with clear and structured analytical insights.
• Maintain high quality governance standards in data reporting and visualization.
• Lead automation of manual data processes through SQL scripts, macros, workflows, and BI tools.
• Maintain secure, scalable fraud databases and ensure data governance and integrity.
• Introduce AI/Gen AI automation capabilities to enhance efficiency, accuracy, and processing speed.
• Collaborate with IT, Business, Product, Compliance, and Operations for fraud-related initiatives and system enhancements.
• Provide analytical support, project insights, and business cases to senior management.
• Support strategic planning, forecasting, and committee reporting through strong analytical and presentation capabilities.

Requirements

• Bachelor’s/Master’s in Finance, Data Analytics, Computer Science, Information Systems, Business, or related fields.
• Certifications in Data Analytics, SQL/SAS/Python, BI Tools, or Fraud Risk (preferred).
• CFE certification is preferable.
• 7–10 years of progressive experience in Fraud Risk Management, Advanced Analytics, MIS, Data Engineering, or Risk Strategy.
• Demonstrated experience leading analytics, automation, or MIS initiatives in a financial institution, payments business, or risk function.
• Prior experience in rule analytics, fraud systems optimization, or advanced data modelling is highly desirable.
• Advanced expertise in SQL, SAS, Python, Power BI, Excel, and data visualization tools.
• In‑depth knowledge of fraud detection platforms (VRM, FraudGuard, or similar rule engines) with capability to analyze, tune, and optimize rules.
• Hands‑on experience in process automation, data pipelines, workflow digitization, ETL concepts, and data warehousing environments.
• Strong command over data governance, data quality control, and secure database management.
• Ability to translate analytical output into strategic recommendations for senior management.
• Strong verbal and written communication skills with the ability to present technical findings in a professional, concise manner.
• Excellent stakeholder management; ability to influence senior and cross‑functional stakeholders.
• High attention to detail and strong analytical thinking.

Tech Stack

• ETL
• Python
• SQL

Benefits

• Health insurance
• Retirement plans
• Professional development opportunities