I am broadly interested in the application of analytical modeling and data analytics in various product and business domains, such as: growth analytics, user profiling, demand forecasting, capacity planning, supply chain management, pricing & revenue management, etc. I enjoy standing at the intersection of business (I interact with business stakeholders and senior leadership team), technology (I write production code), and math (I build complex stats/optimization/machine learning models). My career passion is to help make product and business operations smarter through innovative and practical analytics. Specialties: • Data science, business analytics, statistics, optimization, stochastic simulation, machine learning • Cross-cultural communication, leadership, program management • Python, R, SQL, Matlab

Senior Data Scientist @ At 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. I have been working on: • Marketplace Optimization: demand prediction, advance supply positioning, etc. • UberEverything (UberEATS, UberRUSH): building intelligent decision systems responsible for demand prediction, menu optimization, supply chain optimization, scheduling, etc.; mobile product analytics, growth hacking, and more. We are hiring: https://www.uber.com/jobs/98842 Contact me if you are interested in Uber! From November 2014 to Present (1 year 2 months) Co-Founder @ July 2015 - present: Board Director July 2013 - June 2015: President July 2012 - June 2013: EVP of Marketing & Product July 2011 - June 2012: Director of Marketing • Cofounded CHAIN 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, fund-raising 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 Present (4 years 6 months) Senior Quantitative Analyst @ 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 tools Side 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) 20% Product Manager @ • 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) Analytics Researcher @ ----------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) Revenue Management Intern @ • 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) Forecast Modeling Intern @ • 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) Industrial Contest Team Leader @ • 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)

Ph.D., Management Science & Engineering @ Stanford University From 2007 to 2011 B.Eng., Information Technology (Automatic Control) @ Zhejiang University From 2003 to 2007 Chen Peng is skilled in: Analytics, R, Entrepreneurship, Statistics, Python, Data Mining, Strategy, Data Analysis, SQL, Optimization, Program Management, Operations Management, Leadership, Operations Research, Business Analytics