Senior machine learning engineer and data scientist with 8 years of experience building and shipping production ML models at leading technology companies. Specializes in large-scale algorithmic optimization, bid threshold modeling for digital advertising platforms, recommendation systems, and growth optimization, with demonstrated ability to translate complex algorithms into production systems achieving measurable business impact at massive scale. Y Combinator-backed founder with deep expertise spanning recommendation algorithms, time series forecasting, customer lifetime value prediction, and large-scale data engineering across multiple industries.
Formal Education
- B.S. in Information Systems and Statistics from Carnegie Mellon University
- Candidate for MBA from MIT Sloan School of Management
Career Highlights
- Designed and deployed a bid threshold model at a major technology company that resulted in substantial cost savings through algorithmic optimization
- Co-founded a mobile paywall company and scaled it to global deployment with significant commercial success
- Built A/B testing and optimization infrastructure deployed globally across numerous customer applications
- Shipped machine learning models controlling news feed, notification ranking, and engagement features at a leading technology platform across multiple products
- Developed growth algorithms at a consumer electronics company that expanded direct-to-consumer revenue through data-driven product strategy
- Head of Algorithm and Machine Learning at an investment evaluation firm, building ML models to evaluate early-stage founders for investment decisions
Expert Qualifications
- Deep expertise in machine learning systems architecture, particularly bid threshold modeling and recommendation algorithms at scale
- Proven ability to translate algorithmic research into production systems with measurable business impact
- Extensive hands-on experience with large-scale data pipeline engineering, inferential statistics, and predictive modeling
- Industry experience spanning digital advertising, mobile applications, consumer electronics, and investment evaluation
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Frequently Asked Questions
What types of cases can this expert support?
This expert can support cases involving machine learning systems, digital advertising platforms, mobile applications, and algorithmic optimization. Their background spans consumer electronics, enterprise software, and data-driven product development, making them particularly useful for disputes around recommendation systems, bid threshold modeling, or A/B testing practices.
What is this expert's technical background?
This expert holds a B.S. in Information Systems and Statistics from a top-tier university and is an MBA candidate at a leading business school. They've built production ML systems for much of their career—designing bid threshold models for digital advertising, shipping recommendation and ranking algorithms at major tech platforms, and co-founding a mobile paywall company that scaled globally. They've also led ML work at a consumer electronics company and an investment evaluation firm.
What technologies does this expert specialize in?
They work primarily with Python for machine learning and data engineering. On the applied side, they specialize in recommendation systems, A/B testing infrastructure, bid threshold modeling, time series forecasting, and notification ranking algorithms. They also have hands-on experience with iOS SDK development, mobile paywall systems, and large-scale data pipelines.
- Machine Learning
- Python
- Recommendation Systems
- A/B Testing Infrastructure
- iOS SDK Development
- Data Pipeline Engineering
- Time Series Forecasting
- Bid Threshold Modeling
- U.S. District Courts
- Patent Trial and Appeal Board