Senior Executive | Financial Crime | Forensic & Financial Crime

• Extract, transform, and analyze large datasets using SQL and Python to support financial crime risk management.
• Design dashboards and reports that provide insights into model performance, alert quality, and operational efficiency.

• Model Validation & Testing

• Conduct

  Above-the-Line (ATL)

  and

  Below-the-Line (BTL)

  testing to evaluate financial crime detection models.
• Perform threshold tuning and scenario calibration to optimize model sensitivity and effectiveness.
• Support model validation exercises, including documentation and reporting of findings.

• Financial Crime Model Support

• Analyze transaction monitoring, sanctions screening, and fraud detection model outputs to identify trends, gaps, and anomalies.
• Recommend enhancements to detection logic, thresholds, and parameters based on testing results.
• Collaborate with model developers and compliance teams to ensure models meet business and regulatory requirements.

• Risk & Compliance Alignment

• Support AML, sanctions, and fraud teams in assessing the effectiveness of controls.
• Document testing methodologies, assumptions, and outcomes in line with regulatory expectations (FATF, RBI, EU, US).

• Continuous Improvement

• Identify process gaps, data quality issues, and opportunities to automate testing and reporting.
• Contribute to the design of reusable scripts, tools, and frameworks for ongoing model monitoring.

Qualifications & Skills

• Bachelor s/Master s degree in Computer Science, Statistics, Data Science, Economics, or related field.
• Proficiency in

  SQL

  (complex queries, performance optimization) and

  Python

  (data manipulation, pandas, numpy, visualization libraries).
• Strong knowledge of

  financial crime compliance domains

  (AML, KYC, Sanctions, Fraud).
• Hands-on experience with

  ATL/BTL testing, threshold tuning, and model calibration

  .
• Analytical mindset with the ability to translate data insights into business recommendations.

• Experience with

  transaction monitoring systems

  (e.g., Actimize, Mantas, NetReveal, SAS).
• Knowledge of regulatory guidelines (FATF, FinCEN, RBI, EU AMLD, OFAC).
• Exposure to machine learning techniques and anomaly detection in the compliance context.
• Familiarity with visualization tools (Tableau, Power BI, Qlik).