Riya Manimaran Email and Phone Number

Designed and implemented advanced data models and performed in-depth analysis using Python, SQL, Databricks and Tableau to extract and deliver actionable insights for strategic decision-making.Streamlined a broker detection model that analyzes customer data (ticket sales, transactions, transfers, etc.) to classify and predict likely ticket brokers, enhancing customer segmentation strategies by converting process from IBM Modeler to an ETL pipeline in Databricks, reducing output time by 99% (from 4 days to 20 minutes).Created detailed documentation for fraud detection model and updates to client data tables, ensuring clarity in processes, data structure, and model usage for future reference and team collaboration.Presented detailed detection model insights and recommendations to leading clients in sports and entertainment industry using Tableau, influencing key business decisions to improve revenue protection and customer management.Initiated creation of a communication channel (Slack) for 100+ senior executives, sharing daily insights from Ticketmaster’s database and guiding department directors across the company with business recommendations.Ensured business continuity by shadowing senior employees and maintaining constant communication with full-time analysts, minimizing risk of disruptions during absences and ensuring smooth operations across the team.Spearheaded a team of six interns to develop and pitch a personal, original innovative product concept for a company-wide innovation contest, utilizing graphic design, product development, and marketing strategies that resulted in winning first place through a compelling digital product mockup presentation to senior executives.

Collaborated with cross-functional teams to gather business requirements and construct thorough specification documents according to legal requests.Performed rigorous Quality Assurance (QA) testing on insurance claims data pulled by data engineers, meticulously verifying its accuracy and consistency to guarantee reliable insights and support data-driven decision-making.Assisted in migrating existing databases in Microsoft Access/Excel and Teradata to improve claims pulling process efficiency, resulting in a 25% reduction in turnaround time for critical tasks.

Conducted qualitative data analysis on data collected from UC Berkeley student tutors involved with Oakland District elementary students to explore further how virtual tutors and young students can efficiently be supported.Developed a comprehensive literature review to provide reference to the current educational climate, identified key existing virtual learning models and insights that impacted project trajectory and focus, demonstrated valuable research skills, and ability to cross-reference information.