Rithvik Segu

Data Analyst @Credit Suisse

US

Designed and implemented predictive models using Python and scikit-learn to identify high-risk transactions, improvingdetection accuracy by 25% and reducing false positives by 15%.• Automated compliance workflows, including report generation and transaction flagging, resulting in a 40% reduction inmanual efforts and enabling compliance teams to focus on high-priority tasks.• Built and maintained interactive dashboards in Tableau and Power BI, providing real-time insights into key metrics likeflagged transactions, compliance risk scores, and operational efficiency.• Consolidated and integrated complex data from internal transactional systems, KYC databases, and external regulatory feedsinto a unified analytics platform using AWS Redshift and Azure Data Lake.• Collaborated with machine learning engineers to fine-tune anomaly detection algorithms, improving overall detection precisionand real-time risk monitoring.• Worked closely with compliance officers to gather feedback, ensuring alignment of the analytics system with evolvingregulatory requirements such as SEC and FINRA.• Reduced compliance reporting time by automating routine tasks, leading to faster, more accurate submissions to regulatoryauthorities and mitigating the risk of penalties.• Supported the compliance team by designing a risk-scoring algorithm that assessed high-risk transactions and clients,reducing the review time for flagged cases by 35%.