Steve Wang

I oversee three key functional areas, driving top-line growth and bottom-line efficiency for DiDi’s international food delivery business:

1. Delivery Operations(acting): Strategic budget planning, pricing frameworks, courier growth & engagement, and marketplace management.

2. Delivery Product: Development of the courier app, pricing and payments systems, service governance, and courier engagement strategies.

3. Marketplace Algorithm: Optimization of Feed, Search, Ads, Dispatch, Surge pricing, and CETA algorithms.

Key Contributions:

• Operational Efficiency: Streamlined budget planning and enhanced spend efficiency through integrated planning, execution, and retrospective processes.

• Courier Loyalty: Designed segmented strategies to retain high-performing couriers, leveraging resource reallocation and innovative product interfaces.

• Surge Algorithms: Improved order throughput and user experience by advancing supply-demand algorithms with enhanced sensing accuracy, decision-making precision, and adjustment mechanisms.

• Feed Optimization: Increased conversion rates by refining personalized recommendations for items and shops.

• Ads Platform: Successfully built an advertising system from the ground up, driving incremental revenue opportunities.

Grew from Individual Contributor to Engineering leader at Uber.

2020–2021: Tech Lead, Intelligent Pricing

• Led the development of real-time optimization solutions for rider and driver pricing, leveraging Machine Learning and Optimization techniques.

• Enhanced marketplace efficiency, contributing to a 5%+ increase in global trips, (approx. 2B+ incremental Gross Bookings) at a flat margin.

• Delivered a scalable product and technology solution that aligned with Uber’s growth strategy.

2017–2020: Tech Lead, Rider & Eater Incentives

• Optimized the cost efficiency of incentive spend through treatment effect estimation and budget allocation optimization.

• Designed and implemented a comprehensive system including BI Dashboards, Campaign Management CRM, and a Causal Learning framework.

• Managed an annual incentive budget exceeding $1 billion, driving measurable business outcomes.

2016–2017: Individual Contributor, Driver Growth

• Developed innovative features to improve driver experience and growth, enabling drivers to better understand earnings and identify high-value opportunities on the platform.

• Contributed to product enhancements that supported Uber’s rapid expansion and driver engagement.

• Software Engineering Intern, Data Infrastructure @ Airbnb (2015): Implemented Druid for data analytics, establishing its initial setup and integrating Druid hooks into Apache Airflow as part of the open-source project.

• Search Engineer Intern @ Baidu Adword (Fengchao) (2014): Enhanced the relevance model pipeline through feature extraction and research, achieving an 8% reduction in false recall.

• Research Scholar @ The Hong Kong University of Science and Technology (2013): Developed ‘Terrain-Toolkit’ and authored a VLDB Demo Paper as the first author.

• Software Engineering Intern @ Microsoft (2012): Designed and implemented an online service anomaly detection tool by analyzing log data.

• Software Engineering Intern @ Morgan Stanley (2012): Created cross-regional trading report tools to improve reporting efficiency.

This marks my “Explore Phase,” a time of curiosity and self-discovery as I navigated through academia and diverse industries to better understand and define my true passions.