Andrew Bageant

Data science lead supporting generative AI features within Instagram Direct Messaging. Defined foundational measurement frameworks, data pipelines, and infrastructure for scaled feature deployment.

• Designed and executed the end-to-end experimentation and product growth roadmap for Instagram Voice Effects; grew it into the #1 generative AI feature within Instagram DM through robust funnel analytics, capacity projections, and opportunity sizing.
• Architected the evaluation plan for generative AI text features in Instagram Direct Messaging, including human evals and scaled auto-evals using LLM judges.
• Leveraged agentic AI tools to rapidly generate sophisticated data analysis, analyze experiments, and automate time-intensive data reporting and monitoring tasks.

Data science lead for monetization features, delivering strategic insights to improve user conversion, optimize creator-subscriber ecosystems, and develop new revenue channels.

• Spearheaded the development of a production content classification system combining human annotation pipelines with machine learning classifiers.
• Architected, trained, and deployed an XGBoost classification targeting model to intelligently trigger feature notifications, significantly lifting conversion rates among high-potential users.
• Developed metrics and experimentation plans for new feature launches totaling $50M+ in annual revenue.

Product data scientist supporting Google Lens; lead for Lens in Google Chrome integrations.

• Partnered with Product, Engineering, and UX leadership to define measurement frameworks and launch strategies across a combined user base of 100M+ DAU.
• Conceptualized, planned, and led a strategic research initiative to classify complex search intent patterns within Chrome browser; delivered behavioral insights that directly steered core feature launches impacting 10M+ DAU.
• Planned and analyzed multi-arm experiments at scale to assess the growth and quality impact of new features, including several Google Lens in Chrome launches that added 1M+ DAU.
• Researched user journeys by analyzing large live-traffic datasets, rater evaluation data, and user survey data using Python (Pandas, NumPy, scikit-learn) and SQL.

Financial analyst supporting revenue planning and global GTM efforts for Google Pixel smartphones.

• Led revenue forecasting and sales data analysis for Pixel smartphone products, building forecasting models in R and Python to guide go-to-market strategies for a product portfolio totaling 10M+ in annual sales.

Principal financial analyst for high-growth Thunderbolt and Ethernet segments ($350M+ annual revenue).

• Analyzed semiconductor market data to inform 5-year pricing and capacity strategies.
• Executed supply chain business development and structured high-impact joint R&D efforts with display and interface hardware suppliers across the US and East Asia. Worked in both English and Mandarin. Ranked in the top 5% of employees company-wide.

Specialization: Artificial Intelligence, Machine Learning, Natural Language Processing, Deep Learning

Cum Laude in Field · Language Citation in Mandarin Chinese