Data Analyst

Company Description

Revas Consulting is a boutique consulting firm specializing in Fraud, AML, and Financial Crime analytics and system implementations. We work with enterprises, fintechs, and high-growth organizations to build scalable fraud and risk management frameworks by integrating analytics, workflow automation, and advanced technologies. Operating at the intersection of data, technology, and risk operations, we help companies transition from fragmented processes to measurable financial crime programs. Our fast-growing team offers deep hands-on analytics expertise, an implementation-driven approach, and senior-level advisory to develop resilient, data-driven solutions. We are committed to empowering organizations to protect customers, streamline operations, and enhance regulatory compliance.

Role Description

We are looking for aData Analyst with strong SQL and Python expertiseto support client engagements across Fraud and AML analytics and system implementation initiatives. This is a hands-on role combining analytics, data engineering support, and implementation validation.

In a startup consulting environment, this role requires adaptability, ownership, and comfort working across multiple projects.

SQL & Data Extraction

• Write complex SQL queries to extract, transform, and validate large datasets
• Perform cross-system reconciliation across core systems, alert platforms, and case management tools
• Support ad-hoc analysis for clients and internal project teams
• Validate scoring models and workflow outputs
  

Python-Based Data Processing

• Use Python (pandas, NumPy, etc.) for:
• Data cleansing and transformation
• Report automation
• Batch processing and validation
• Risk Modeling
• Build reusable scripts to streamline data validation processes
  

System Implementation Support

• Assist in data mapping and data model validation during fraud/AML platform implementations
• Support historical data ingestion and transformation
• Participate in UAT testing and validate system outputs
• Document transformation logic, data lineage, and reporting definitions
  

Reporting & Operational Metrics

• Develop dashboards and operational reports
• Regulatory reporting support metrics
• Ensure reporting accuracy, traceability, and audit readiness

Qualifications

• 36 years of experience in Data Analytics, Fraud Analytics, AML Analytics, or Risk Analytics
• Strong hands-on SQL (joins, aggregations, CTEs, window functions)
• Strong Python skills (pandas required)
• Experience working with large structured datasets
• Strong analytical and problem-solving skills
• Ability to work independently and manage competing priorities

Work Requirements

• In-office role (mandatory)
• Shift timing: 2:00 PM 10:00 PM IST
• Ability to collaborate with global clients and cross-functional teams
• Comfortable working in a fast-paced startup consulting environment