Yun Huang

Work
- Focused on scaling pricing, monetization, and applied ML products across large-scale (>$xB) commerce and advertising systems
- Highlights include launching eCommerce pricing products at Jet.com ($3.3B acquisition) and ML-enabled products at LinkedIn
- Recently lectured at Penn (Course ID: OIDD245), focused on how firms evaluate rule-based vs. ML features in mitigating online price wars
- See full work milestones below
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Personal
- I'm a U.S. Citizen. Native fluency in English & Cantonese
- Writers I admire include Noah Smith, Nick Bostrom, and Immanuel Kant. I enjoy science fiction films which provoke thoughts about the complexities of human life, such as The Three-Body Problem and The Prestige‍
- In my free time, I enjoy distance running, reading, investing in real estate, making coffee
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Interests & Personal Philosophy
- Data: I believe the demand for high-quality training data is underestimated, and we will see the rise of data brokerage markets for AI
- Compute: Compute will drive not only decisions on what should be built, but what actually ships
- AI Research: I follow work on alignment and interpretability research
- Application: I'm tracking how core research labs vs. independent entities will faire in scaling real-world commercial adoption
- Life: I believe that your environment—especially your social and informational networks—shapes who you become more than your conscious choices do. What feels like “intentionality” is often just the emergent effect of subtle, repeated training signals from the people and structures around you

Work Milestones Full List
- 05/2025: Guest Lecturer, Machine Learning Application, Delivered a lecture to 500+ in Penn’s Machine Learning Application curriculum, focused on trade-offs between rule-based and ML products in mitigating online price wars
- 03/2024: AI Adoption at LinkedIn, Led development of one of LinkedIn’s first internal AI prompt libraries, enabling multiple production use cases and broad internal adoption
- 06/2024: Macro Risk Detection & Forecasting (Ukraine War), Identified early signals of advertiser spend pauses during the Ukraine War; operationalized pause-detection signals across core forecasting workflows, improving accuracy and mitigating material revenue risk
- 05/2024: Lead Scoring Product (ML): Lauche ML-enabled lead-scoring feature embedded in forecasting product, incorporating external data sources and improving conversion among adopted teams
- 01/2023: Joined LinkedIn to steer monetization and ML-enabled initiatives for fastest-growth vertical (> $xB Advertising unit)
- 08/2021: Promoted to Pricing VP Chief of Staff within 6 months. Supported roadmap execution across ~$40B GMV, coordinating 30+ stakeholders across Product, Data Science, and Engineering
- 10/2020: First residential investment in the Greater New York area
- 02/2020: Led evaluation of rule-based versus ML products in mitigating online price wars. Deployed a rule-based system achieving ~2× profitability at ~1/5 of projected resourcing. Built anomaly-detection dashboards identifying ~70% of falsified pricing cases, preventing ~$xM in losses.
- 09/2018: Joined Jet.com ($3.3B acq.), Managed $120M P&L. Launched one of Jet’s first inventory analytics products, reducing access latency from days to minutes, increasing supply availability from ~80% to ~95% within weeks. <1% of Cohort to receive accelerated progression & VP placement in Pricing
- 2017: Conducted research under Professor Maurice Schweitzer on how emotional states affect decision-making under uncertainty
- 2017: Co-developed one of The New York Times’ first short-audio products, increasing engagement for 'The Daily Podcast'
- 2014–2018: University of Pennsylvania, B.A. in Economics & Psychology (Focus: ML Application). Awarded full $240K merit-based scholarship; Dean’s List
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