Chen Peng's Email Addresses & Phone Numbers

📖 Summary

Senior Data Scientist II @ Uber November 2014 - January 2016: Senior Data Scientist I As a data scientist at Uber I worked on:• Marketplace Optimization for ride sharing: demand prediction, advance supply positioning, etc.• Uber Everything (Uber Eats, Uber Rush): building intelligent decision systems and models responsible for demand prediction, menu optimization, ranking, batching & scheduling, etc.; mobile product analytics, growth hacking, and more. From November 2014 to March 2016 (1 year 5 months) San FranciscoAnalytics Researcher @ Intel Corporation ----------PhD research project----------• Developed a dual-mode equipment procurement strategy/heuristic with three stages: contract negotiation, capacity reservation, and order execution • Implemented the strategy for the 45nm lithography tool and decreased the equipment procurement lead time by up to two quarters • Presented the project twice to the VP of TMG at Intel; the estimated annual savings on capital procurement exceed tens of millions of dollars• Constructed a detailed business “scenario bank” through interviews and surveys at Intel, which includes 200+ root causes of risk scenarios and 10+ reactive and proactive strategies for each possible scenario• Developed a “reactive dashboard” and a “proactive dashboard” that can quantitatively evaluate the impact of scenarios and effect of actions based on underlying analytical models; this decision support tool is used at Intel to manage operational risks during product transitions From September 2008 to April 2011 (2 years 8 months) Santa Clara, CARevenue Management Intern @ Nor1, Analytics Department • Empirically identified the existence of customer loyalty using more than 1 million historical transaction records obtained from Nor1’s hotel-chain clients • Developed a new pricing and room allocation heuristic that incorporates guest loyalty status as an input; the heuristics estimated impact on clients’ long-term revenue is a 3-5% increase From June 2010 to August 2010 (3 months) Sunnyvale, CAForecast Modeling Intern @ Intrigo Systems Inc • Designed a correlation engine to extract future demand information from online consumer ‘sentiments’ (ratings, comments); utilized this information to improve clients’ demand forecasts• Implemented the prototype model with an Intrigo client and achieved a 20% decrease in average forecasting error From June 2009 to September 2009 (4 months) San Mateo, CAIndustrial Contest Team Leader @ L'Oréal, Industry Division • Organized and streamlined a demand-driven supply chain to meet capacity increase in L'Oreal; built a managerial system to monitor operations and performance of the chain• Presented the plan to an international jury at Paris, France; won second place in the international final of 2006 L'Oreal Ingenious Contest, competing against 47 teams from six countries. From November 2005 to February 2006 (4 months) Shanghai, China; Paris, FranceAngel Investor & Advisor @ Self On the side I do angel investment and advise early stage startups in the fields of data, AI, marketplaces, etc. If you are a startup founder in the above areas and want feedback / inputs on your endeavor, hit me up. Co-Founder @ China America Innovation Network July 2015 - present: Board Director July 2013 - June 2015: PresidentJuly 2012 - June 2013: EVP of Marketing & ProductJuly 2011 - June 2012: Director of Marketing• Cofounded CHAIN (http://www.innovationchain.org/) in 2011 with the goal of building a cross-border platform to promote entrepreneurship and innovation in both U.S. and China. As a non-profit organization, we are powered by a team of passionate volunteers, successful entrepreneurs, business professionals and engineering wizards. CHAIN network currently connects 9000+ members in both Silicon Valley and China, and includes more than 30 partner organizations (www.innovationchain.org)• Led a core team of 20+ talented volunteers to execute on event planning and delivery, branding and marketing, partnership and alliance, fundraising and operations, etc. • Together with the team delivered more than 40 entrepreneurship-oriented events (panel discussions, startup bootcamps, video pitches, etc.), including 4 large-scale annual conferences in China From July 2011 to June 2015 (4 years) Silicon ValleySenior Quantitative Analyst (Data Scientist) @ Google September 2011 - March 2014: Quantitative Analyst• Developed data-driven policies, models, and decision-support tools to improve the efficiency and economy of Google’s global cloud infrastructure and platform, such as: conducting demand forecasting and capacity planning based on the company’s traffic and resource usage growth; measuring compute resource stranding via large-scale monte carlo simulation models; resource oversubscription through leveraging the usage multiplexing effect; improving the VM scheduling algorithm, instance type offering, and pricing strategy for Google Compute Engine, etc.• Communicated findings to senior executives and collaborated with engineering/product stakeholders to drive adoption of recommendations, policies, and toolsSide Projects:• Improved sales forecast for various hardware products (Nexus phones, tablets, Chromecast, etc.) through building predictive models that leverage search query and ads click signals From September 2011 to November 2014 (3 years 3 months) Mountain View, CA20% Product Manager @ Google • Interviewed internal Google Cloud Platform (GCP) stakeholders (product managers, engineers, sales, finance, etc.) and external Cloud customers (EA, Egnyte, etc.) to collect and synthesize their requests for BI metrics• Developed PRD to define a unified BI tool based on RESTful API that would allow systematic access to revenue, billing, and usage metrics of GCP, including advanced analytical features such as anomaly detection and usage pattern clustering• Defined feature release cycles and pitched to both product and engineering teams to get buy-in From January 2013 to April 2013 (4 months) Mountain View, CAHead of Data @ Faire Faire is building a B2B e-commerce marketplace to help independent retailers (both brick+mortar and online ones) shop millions of products from brands and makers in a risk-free manner. We are also offering various technology solutions to help our customers streamline their business operations. We believe in using digital transformation of the value chain to empower small business owners & entrepreneurs to thrive and win because it is good for both the economy and the humanity overall.As a unicorn, Faire is backed by Sequoia Capital, Y Combinator, Lightspeed Ventures, Founders Fund, Forerunner Ventures, DST Global, etc. Our GMV is growing ~3X YoY at the moment.In the data area we are currently hiring:- data engineering manager (https://lnkd.in/esKXySy)- senior data engineer / ML engineer (https://lnkd.in/eCNb2jX) - senior/lead data scientist for search & ranking (https://lnkd.in/e69rd_e)- senior/lead data scientist for experimentation & inference (https://lnkd.in/eCva2ee)- data scientist for marketplace efficiency- product analyst (https://lnkd.in/eCBga2u)and many other roles: https://lnkd.in/ed5sPJ3Ping me if interested in learning more! San Francisco Bay AreaDirector, Head of Data Science & Analytics, Uber Eats @ Uber March 2019 - June 2020: Director, Data ScienceAugust 2017 - February 2019: Senior Manager, Data ScienceMarch 2016 - July 2017: Manager II, Data ScienceAt Uber we are building the technology and platform to power the on-demand urban transportation and logistics marketplace, at a global scale, with extreme efficiency, scalability, and reliability. Officially launched in late 2015, Uber Eats is a fast-growing meal & grocery delivery service that currently operates in more than 40 countries and thousands of cities worldwide and serves millions of users, merchants, and delivery partners.As a founding team member of Uber Eats, I built from the ground up, and led the Uber Eats data science & analytics team of 90+ geniuses---data scientists, product analysts, and strategy analysts---across multiple office locations (SF, NYC, Toronto, Hyderabad, etc.). My team powered the Eats business to grow from a few hundred orders per day to over $25 billion annual GMV run rate over 4.5 years. We tackled the following difficult & fun problems associated with Uber's three-sided delivery marketplace:- personalized ranking, search, and recommender systems for restaurants and menu items- meal preparation time, waypoint time, and end-to-end delivery time prediction - dispatch, batching, scheduling, vehicle routing, and general network optimization- demand & supply forecasting, driver positioning, structural & dynamic pricing, delivery zone optimization- marketing spend & growth optimization- restaurant and enterprise analytics- Ads ranking - customer support analytics- ...Cutting-edge techniques in machine learning, statistical modeling, convex & combinatorial optimization, hypothesis testing, causal inference, and behavioral economics, etc. were frequently utilized in our work. From March 2016 to June 2020 (4 years 4 months) San Francisco