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Kun Zan

Project Lead - Joint Industry Project

Sr. Manager of Data Science at Expedia Group

Austin, Texas

Section title

Kun Zan's Email Addresses & Phone Numbers

Kun Zan's Work Experience

Weatherford

Project Lead - Joint Industry Project

August 2012 to 2013

US Army Corps of Engineers, Risk and Decision Science Team

Decision Analyst Intern

May 2010 to August 2010

HomeAway

Staff Data Scientist - Dynamic Pricing

September 2016 to February 2017

Kun Zan's Education

Huazhong University of Science and Technology

Master, Industrial Engineering

Beihang University

Bachelor, Mechanicl Engineering

The University of Texas at Austin

PhD, Operations Research

About Kun Zan's Current Company

Weatherford

• Perform risk analysis for Managed Pressure Drilling, funded by Weatherford International. The main work includes probabilistic modeling using influence diagram, deriving higher order conditional dependence structure, sensitivity analysis, and mining reliability information as inputs of the model from large data sets

About Kun Zan

📖 Summary

Project Lead - Joint Industry Project @ Weatherford • Perform risk analysis for Managed Pressure Drilling, funded by Weatherford International. The main work includes probabilistic modeling using influence diagram, deriving higher order conditional dependence structure, sensitivity analysis, and mining reliability information as inputs of the model from large data sets From August 2012 to 2013 (1 year) Decision Analyst Intern @ US Army Corps of Engineers, Risk and Decision Science Team Worked on quantitative consulting projects. Implemented decision analysis, optimization, value of information analysis, Monte Carlo simulation; used computer tools including the open source optimization solver (GLPK) and @Risk to solve math models, some of which were coded in VBA. From May 2010 to August 2010 (4 months) Staff Data Scientist - Dynamic Pricing @ HomeAway • Revenue management system for all vacation rental property owners• End to end experiences of data science products at scale, including deployment in prod, operations and experiments. From September 2016 to February 2017 (6 months) Sr. Data Scientist - Ranking @ HomeAway • Designed, developed and implemented the company’s first machine learning driven ranking model to increase booking acceptance rate• Designed, developed and implemented the ranking models to increase to increase page view conversion and inquiry conversion• Data ETL for ranking training, using Spark and Scala• Mentored junior data scientists, and coached UT Business school master student capstone projects From April 2015 to September 2016 (1 year 6 months) Sr. Data Scientist @ HomeAway • Develop a digital marketing attribution model, using visitor’s full click stream history. It clearly identifies the underestimated/overestimated attributions• Develop and implement the first lead scoring model in the company for new customer acquisition.• Develop and implement a up-selling model to increase the average selling price.• Develop a sorting method for the marketplace prioritization. From June 2013 to April 2015 (1 year 11 months) Graduate Research Assistant @ University of Texas at Austin • Dissertation “Value of Information and Portfolio Decision Analysis”. Develop mathematical model, investigate properties and optimization issues of value of information in portfolio settings, and develop methods of portfolio decision analysis. The tools are mainly decision analysis, dynamic programming, Bayesian inference, Order statistics, probabilistic modeling. From August 2008 to July 2013 (5 years) Teaching Assistant @ University of Texas at Austin Operations Research, and McCombs School of Business: Engineering Finance; Elementary Business Statistics; Operations Management; Decision Analysis: Gave lectures, led problem sessions, held office hours, and graded assignment. From January 2011 to May 2012 (1 year 5 months) Project Lead - Joint Industry Project @ Drillinginfo • Develop a statistical and computational method to predict the unconventional oil and gas production of the undeveloped acreage given observed geological data with a team. The first step is to use generalized additive model, including thin plate regression splines, kriging, to predict the geologic characteristics. The second step is to use a regression with regularization model to prediction unconventional oil and gas production. The methods are written in R, and developed a private R package.• Lead the team in charge of communicating with DrillingInfo CTO, the analytic team and business development people, demand analysis, and project management. From January 2013 to May 2013 (5 months) Sr. Manager of Data Science - Marketplace Optimization @ HomeAway • Lead Marketplace Optimization Data Science team working closely with product, engineering and UX design teams to research, develop and deploy ML/DS solutions.• Provide machine learning and data science solutions for several star products, such as MarketMaker, Rent Potential, Boost, Market Dynamics, Competitive set, Fee tests, serving HomeAway 2+ million properties• Methodology: Machine learning, optimization, statistics, causal inference and data analytics• Drive data science vision in the Marketplace product strategy• Guest lecture of University of Texas at Austin Business School, Engineering School graduate courses From August 2018 to October 2019 (1 year 3 months) Sr. Manager of Data Science - Marketplace Optimization @ Expedia Group Lead the effort of research, develop and deploy machine learning and data science solutions for:• vacation rental platform monetization • Vacation rental marketplace disruptive products• Vacation rental and hotel dynamic pricing and revenue management• Travel marketplace dynamics• Methodology: Machine learning, optimization, statistics, causal inference and data analytics Data Science Manager - Marketplace Optimization @ HomeAway • Lead the team to research, develop and deploy all machine learning and data science solutions for the large-scale vacation rental revenue management (dynamic pricing) system, MarketMaker. The experiment results demonstrate it has increased customer revenue by $xxx.• Lead the team designed and developed the very first vacation rental potential model to access the rent potential. It is one of the most leveraged data science products at the company, supporting supply acquisition, Partner success, Marketing.• Lead a large-scale casual effect experiment on monetization, which served as the base for the following tests, which brought several million revenue. The work is summarized into a paper for submission.• Hire, mentor and develop the Marketplace Optimization team from scratch From February 2017 to July 2018 (1 year 6 months)


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Frequently Asked Questions about Kun Zan

What company does Kun Zan work for?

Kun Zan works for Weatherford


What is Kun Zan's role at Weatherford?

Kun Zan is Project Lead - Joint Industry Project


What is Kun Zan's personal email address?

Kun Zan's personal email address is p****[email protected]


What is Kun Zan's business email address?

Kun Zan's business email addresses are not available


What is Kun Zan's Phone Number?

Kun Zan's phone (214) ***-*244


What industry does Kun Zan work in?

Kun Zan works in the Internet industry.


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Kun Zan's Personality Type

Extraversion (E), Intuition (N), Feeling (F), Judging (J)

Average Tenure

1 year(s), 5 month(s)

Kun Zan's Willingness to Change Jobs

Unlikely

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