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Business Analyst L4

Job in Irving, Dallas County, Texas, 75084, USA
Listing for: Wipro
Full Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 60000 - 135000 USD Yearly USD 60000.00 135000.00 YEAR
Job Description & How to Apply Below

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world.

For additional information, visit us at

Job Description:

BA with Fraud Exp

We are seeking an experienced Business Analyst with deep expertise in the Fraud Management domain and strong exposure to Analytics & Reporting. The ideal candidate will work closely with business stakeholders, fraud operations teams, product owners, and technology teams to drive fraud monitoring, analytics, reporting, and strategic initiatives. The candidate should be capable of translating complex business requirements into actionable insights and data-driven solutions.

Key Responsibilities

Partner with Fraud Operations, Risk, Compliance, and Technology teams to gather, analyze, and document business requirements.

Drive fraud analytics initiatives to identify trends, emerging fraud patterns, operational gaps, and process improvement opportunities.

Create detailed business requirements, functional specifications, process flows, use cases, and user stories.

Define and track fraud-related KPIs, KRIs, operational metrics, and management reporting.

Develop executive dashboards and analytical reports using tools such as Power BI, Tableau, or similar BI platforms.

Perform root cause analysis on fraud incidents and recommend mitigation strategies.

Work closely with data engineering and technology teams to define data requirements and reporting solutions.

Support fraud detection, monitoring, and risk management programs through data-driven insights.

Participate in UAT planning, test case preparation, execution, and business sign- off.

Present analytical findings and recommendations to senior management and executive stakeholders. Ensure compliance with regulatory, audit, and risk management requirements.

Qualifications

Bachelor's or Master's degree in Business, Finance, Computer Science, Information Systems, or related field.

  • 12+ years of experience in Business Analysis with significant exposure to Fraud, Risk, Analytics, and Reporting initiatives within Banking/Financial Services. Nice to Have for Citi/OMAI-Type Engagements
  • Experience supporting Fraud Strategy, Fraud Controls, Risk Monitoring, Executive Reporting, and Data Analytics programs. Internal - General Use
  • Exposure to enterprise data platforms, cloud analytics solutions, and AI/GenAI- driven fraud detection initiatives.
Required Skills
  • Strong experience in Banking Fraud Management, Fraud Operations, Risk Analytics, or Financial Crime domains.
  • Expertise in requirements gathering, business analysis, stakeholder management, and solution design.
  • Strong analytical and problem-solving capabilities.
  • Hands-on experience with SQL for data analysis and reporting.
  • Experience with Power BI, Tableau, Cognos, Business Objects, or similar reporting platforms.
  • Strong understanding of fraud metrics, fraud controls, case management, and fraud monitoring processes.
  • Experience working in Agile/Scrum environments.
  • Excellent communication and presentation skills.
Preferred Skills
  • Experience with credit card, payments, digital banking, wire fraud, AML, or transaction monitoring.
  • Knowledge of data warehousing and data modeling concepts.
  • Exposure to predictive analytics, machine learning, or AI-driven fraud detection…
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