Mary Sheeba Theodore

Contributed in building an analytics pipeline consolidating driver data from 5+

• • platforms (Uber, Bolt, Lyft and others) into a single weekly report tracking active drivers, trip volume, fare and net income for 5,000+ users across the ecosystem. Surfaced root causes of engagement and retention drop-offs by analysing behavioural signals across platforms, turning raw database queries into structured trend insights that drove proactive product decisions. Implemented a threshold-based anomaly detection framework monitoring weekly driver activity, fare and income signals, flagging outliers for verification before each partner report, cutting manual QA time for the internal team.

Designed key metrics and owned end-to-end dashboard development in Looker,

• • tracking booking funnel performance and NPS, a single source of truth for product, ops, and business teams. Wrote SQL queries and Python scripts to create and maintain aggregated data tables, simplifying data querying across the organisation and improving reporting speed by 50%. Improved A/B testing frameworks with product and engineering, analysing results and communicating conclusions that directly accelerated feature decision. Promoted data literacy across teams by organising data reviews and adapting analytical communication to technical and non-technical audiences.

Wrote and optimised SQL queries across complex databases handling millions of

• • financial transactions daily, building hands-on SQL expertise across large-scale data environments Designed and maintained aggregated data views and validation pipelines across multiple platforms, ensuring cross-platform KPI consistency and data accuracy for institutional stakeholders Bridged business and technical teams as a BA in agile environments, identifying root causes of data issues and ensuring functional accuracy across major release cycles