- Lead a distributed organization of 50 professionals, encompassing software engineering, data science, RF engineering, analytics, and product management teams.- Drive innovation in geospatial analytics, data science, and remote sensing to optimize tower inventory, predict future demand, and create new revenue opportunities.- Oversee development of the company's Atlas (Lightning) network planning tool, utilizing advanced geospatial algorithms for network expansion modeling.- Spearhead machine learning projects, including lifetime asset valuation models and tower demand/supply models, harnessing geographic data to support business strategy.

- Built and scaled Twitter’s User Signals organization, with a focus on geolocation, user embeddings, and trust and safety—achieving a 2.5% revenue increase and 750K user growth.- Led Geo Atlas, a deep learning model that reduced user location error by 65%, powering ad targeting and recommendation systems.- Partnered with research to develop TwHIN, Twitter’s graph-based user embedding system, used to improve content and ad recommendations by embedding the social graph.- Partnered with Trust & Safety to enhance Agatha, Twitter’s primary trust and safety platform, achieving 10x performance improvements for near real-time monitoring.- Increased ad revenue by $40M through strategic improvements to geolocation and ad-targeting pipelines and optimized system integrations.

- Grew a new engineering team of 25, partnering with data science on pricing, forecasting, and promotions for Wayfair’s extensive product catalog.- Enhanced Wayfair’s pricing engine, adding competitor-driven demand models and a market similarity model that supported better price positioning.- Developed critical infrastructure, including a feature store and A/B testing framework, improving efficiency and model deployment for data scientists.- Led impactful projects like the true market value estimation and badge optimization, helping Wayfair optimize demand forecasting and pricing decisions.- Spearheaded the adoption of Spark and big data infrastructure, enabling scalable, data-driven strategies

Led multiple teams to build custom trading and portfolio management systems. Innovative leadership of hybrid teams consisting of software developers, quants, and equity data specialists. Played a lead role helping the firm move to big data technologies. Tech stack includes C#, ms sql, hadoop/spark, and python.

Responsible for a custom portfolio management and trading system, used by GMO’s partners and senior portfolio managers.

Business development and technical leadership for IMP's technical practice. Individual contributor and project manager for front-office technology projects, including order management system upgrades and implementations.