Role: Lead, Data Integration (through Surf)
Timeline: June 2022 – November 2024
Focus: Startup Intelligence, Data Refinement, Use Case Development
Stack: Python (data cleaning), Social Media APIs, Performance Metrics Mapping

As part of a contract engagement with Sequoia’s early-stage scouting division, I led a data-driven initiative to identify promising startups using real-time social media insights from platforms like Instagram and Twitter.

The mission was clear: turn noisy, unstructured social data into targeted investment signals that could support strategic decisions — helping Sequoia stay ahead of market trends and founder activity.

• Data Sourcing & Structuring: Collaborated with Sequoia’s internal data team to refine and structure scraped social media data, ensuring accuracy, recency, and contextual relevance for trend tracking.

• Startup Signal Mapping: Designed a framework to track startup activity levels, engagement patterns, and audience traction to distinguish between noise and meaningful traction.

• Use Case Development: Built a series of targeted scouting use cases based on company growth markers, enabling more informed outreach and portfolio filtering.

• Actionable Insight Delivery: Translated raw data into digestible reports and dashboards, arming the investment team with clear insights on which startups were gaining ground and why.

This project combined my love for pattern recognition with productized intelligence — a perfect example of how great data, when framed right, can sharpen instinct and accelerate innovation.