Teams at Scribd, Inc.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.

Design and implement features for content ingestion pipelines, metadata services, and content processing workflows. Build reliable, observable services that handle diverse file formats, malformed inputs, retries, and asynchronous workflows. Collaborate with ML, Search & Discovery, and Product to improve metadata extraction, classification, and discoverability while leveraging LLM-based tools and AI-driven practices.