Sailesh Suresh

I’m a Data Analyst with 4+ years of experience in marketplace analytics, operational excellence, and supply-side strategy, including hands-on experience in Uber’s Earner Operations. I focus on marketplace dynamics, driver behavior, onboarding funnels, engagement, churn, incentives, and marketplace reliability to create real business outcomes.

At Uber (Via Indium Software), I led analytics initiatives to identify and prevent driver- and rider-side fraud, building Python-based automated detection rules and preventive guardrails. I also engineered GenAI-powered analytics agents that integrated into analyst workflows, automating ~70% of recurring query generation to improve efficiency and enable higher-value insights.

I built an automated fraud mitigation system that prevented payouts to fraudulent users, delivering approximately $3M in annual cost savings. I also remediated a system gap around unlimited arrears, reducing financial exposure and delivering approximately $400K in annual savings, while consolidating key metrics into a single stakeholder-facing view for faster, clearer interpretation.

Before that, I worked as a Data Engineer at Altimetrik, refactoring Snowflake stored procedures with Python and SQL (up to 35% faster execution), strengthening data reliability with Python-based automated tests, and building ETL pipelines into a centralized Data Lake. I bring a practical, growth-minded approach—using data engineering rigor, experimentation, and AI tools to automate analysis and improve how teams operate.