Hariharan Agaranallur Ganesan

Integrated Surveillance Department

• Engineered large-scale risk detection pipelines across 13+ market domains using Python, PySpark, Hive, and Teradata, supporting high-volume regulatory surveillance.
• Reduced overall detection and processing latency by 83%, enabling rapid identification of high-risk activities through optimized data workflows and tooling enhancements.
• Developed Python-based abuse detection systems to flag behaviors such as front-running, circular trading, and abnormal trading patterns, modernizing legacy SAS rule logic into automated pipelines.
• Created machine learning–based dynamic thresholding models to reduce false positives, and improve the accuracy and consistency of alerts across surveillance cases.
• Led a three-member team in migrating complex enforcement logic to PySpark, resolving schema conflicts, and optimizing Hive/Teradata queries for stability and performance.

Investigations Department

• Designed full-stack trade analytics dashboards for PFUTP investigations, improving reviewer consistency, and enabling policy-aligned decision-making for complex behavioral cases.
• Built the Corporate Announcements Trading Pattern Tool to classify events and generate structured pre- and post-announcement behavioral insights, strengthening PIT investigations.
• Supported senior investigators by translating ambiguous case facts into clear policy interpretations, improving enforcement clarity, reviewer alignment, and documentation quality.

• Co-developed and customized SAP ERP modules across finance, inventory, and operations workflows, streamlining core business processes, and achieving a 30% improvement in operational turnaround time for enterprise clients.
• Collaborated with cross-functional teams to translate business requirements into scalable SAP solutions, reducing manual workload, and contributing to an estimated $500K annual cost savings through automation and process optimization.
• Conducted in-depth data analysis and stakeholder interviews to identify inefficiencies and recommend corrective actions, improving client decision-making accuracy and forecasting reliability by 25%.
• Built reusable functional documentation, test cases, and configuration guides, enabling faster onboarding, and reducing post-deployment defects across SAP modules.
• Served as a primary liaison for key accounts, maintaining a 95% client retention rate through proactive communication, timely issue resolution, and strong relationship management across technical and functional teams.
• Led UAT cycles, coordinated user training, and resolved production issues, ensuring smooth adoption of new features and minimizing business disruption during rollouts.