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William Whipple Neely

Data Science, Taking Some Time Off

Data Science, Taking Some Time Off at Self Employed

Redwood City, California

Section title

William Whipple Neely's Email Addresses & Phone Numbers

William Whipple Neely's Work Experience

Self Employed

Data Science, Taking Some Time Off

Electronic Arts (EA)

Director of Data Science

April 2014 to December 2017

San Francisco Bay Area

PopCap Games

Senior Statistician

June 2010 to April 2014

William Whipple Neely's Education

University of Washington

Ph.D, Mathematics

1988 to 1994

Hampshire College

BA, Biochemistry

1980 to 1984

University of Wisconsin-Madison

Ph.D, Statistics

2004 to 2009

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Methodical
Tough
Loner

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52% Left Brained
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William Whipple Neely's Estimated Salary Range

About William Whipple Neely's Current Company

Self Employed

Frequently Asked Questions about William Whipple Neely

What company does William Whipple Neely work for?

William Whipple Neely works for Self Employed


What is William Whipple Neely's role at Self Employed?

William Whipple Neely is Data Science, Taking Some Time Off


What is William Whipple Neely's personal email address?

William Whipple Neely's personal email address is w****[email protected]


What is William Whipple Neely's business email address?

William Whipple Neely's business email addresses are not available


What is William Whipple Neely's Phone Number?

William Whipple Neely's phone (213) ***-*224


What industry does William Whipple Neely work in?

William Whipple Neely works in the Internet industry.


Who are William Whipple Neely's colleagues?

William Whipple Neely's colleagues are Adam Reid, Jelle Prins, Victor Pena, Zlatan Menkovic, Femke Schoonhoven, Lucie Vojtova, Karthik Hariharan, Guocheng Xie, Stephen H., and Robert Greer


About William Whipple Neely

馃摉 Summary

Data Science, Taking Some Time Off @ Self Employed Director of Data Science @ Electronic Arts (EA) As Director of Data Science at EA I have built and mentored a data science team from the ground up. The team includes computer scientists, statisticians, economists. Our group forecasts customer lifetime value, does text analysis of open ended survey responses, creates match making algorithms, recommender systems, and uses machine learning to segment customers and predict future behavior. In order to address the fact that data scientists are also creators of software, our group has also created software tools for data scientists and analysts that are used throughout EA. In addition we collaborate with academic researchers at multiple universities. From April 2014 to December 2017 (3 years 9 months) San Francisco Bay AreaSenior Statistician @ PopCap Games I founded the PopCap Analyics team. In this role I served as supervisor and statistical consultant for a team of analysts working with business and game data for online and mobile games. Because of the difficulty in finding skilled analytics professionals, much of my supervisory work has involved hiring and training analysts. This strategy of building an analytics team through training has been highly successful. Beyond training new analysts, my work at PopCap includes building models for user behavior on an individual and a cohort level, Life Time Value (LTV) models, customer retention models, and customer segmentation models that use both statistical and machine learning techniques. I have also been a key contributor to the process of improving our internal metrics systems, and manage our relationship with the external metrics provider Kontagent. From June 2010 to April 2014 (3 years 11 months) Research Assistant @ Center for Demography and Ecology, University of Wisconsin-Madison In this position I applied the methodologies developed in my statistics dissertation to the analysis of data from a Respondent Driven Sampling (RDS) survey of female sex workers in Shanghai, China. RDS is a variant of snow-ball sampling and is currently the most popular chain-referral method used to gather data from hidden populations. This application of my dissertation work was presented at the annual Population Association of America conference in May 2009. I was the author of the statistical methodology section of the grant proposal that funded this position. From September 2008 to February 2009 (6 months) Research Assistant @ Department of Statistics, University of Wisconsin-Madison This was a project to develop an R package that provides methods for carrying out Bayesian model selection for QTL models. My duties included writing an extensive R-vignette on novel genome scan methods, developing software in R and providing software project management consulting. From September 2005 to August 2006 (1 year) Teaching Assistant @ Department of Statistics, University of Wisconsin-Madison I served as TA for Statistics 371. This is an introductory statistics course designed to serve the needs of students studying the life sciences. The topics covered include the elements of basic statistics; normal, binomial and poisson distributions; hypothesis testing and elementary experimental design. From September 2004 to May 2005 (9 months) Research Associate @ Fred Hutchinson Cancer Research Center This was a post-doc level position in which I worked with an interdisciplinary genomic research team in the Public Health Sciences division of Fred Hutchinson Cancer Research Center. Specific duties included assisting principal investigators and lead statistician in the design of statistical analyses; writing project reports, scientific papers and grant applications. I also developed and designed statistical software and provided computational, mathematical and statistical consultation to other researchers. Specific projects include developing and implementing models for nonlinear regression of microarray time-course data associated with the yeast cell cycle; developing generalized additive models for studying the association of local gene expression levels with the sites of viral gene insertion; and developing algorithms and C/C++ code for computing smoothing splines. From June 2002 to June 2004 (2 years 1 month) Senior Biostatistician @ Enodar Biologic Corporation I served as a scientific/technical liaison between research scientists at Fred Hutchinson Cancer Research Center and marketing and development personnel at Enodar, managed projects for SBIR (small business innovation research) grant funded development of novel genomic analysis software, provided statistical consulting to customers carrying out complex genomic analysis of mRNA microarray data. From June 2002 to August 2003 (1 year 3 months) Research Scientist/Chief Software Architect @ Talaria Inc. I served as lead computer scientist and consulting mathematician for teams developing statistical and multimedia software for grant funded research projects, served as a consultant providing design and development expertise to university researchers wishing to build web-based intelligent tutoring and assessment systems. Projects included developing a statistical package for interactive Bayesian analyses of randomized clinical trials; ProPurview, a graphical statistical package for performing projection pursuit; AIDAS, a conversational simulator to help clinicians learn how to help terminally ill patients; Sim II, a multimedia simulator to teach clinicians pain management skills; DIANA II, web-based software for facet-based learning; Taking Charge of Chronic Pain, web-based multimedia software for teaching about issues related to the management of chronic pain. I also served as acting Chief Technology Officer (CTO) and hired a permanent CTO. While at Talaria I also served as a grant reviewer for the National Science Foundation's small business innovation research grants (covering educational software for math and science) and served as interim principal investigator for two NIH funded research projects: MetaSim, a system for rapid development of medical simulations; and FACT, a software package for performing functional data analysis and nonlinear regression. From March 1998 to April 2002 (4 years 2 months) Senior Software Engineer & Applied Mathematician @ Advanced Marine Technology At Advanced Marine Technology I developed commercial software for marine navigation. Specific duties included developing algorithms for computer graphics, Kalman filtering of noisy sensor data and mathematical cartography. I also served as consulting mathematician to other software engineers and hardware engineers. I was also project manager for this company's transition from procedure based software design to object-oriented software. As part of this project I designed a software development kit (SDK) for cross-platform development of navigational applications under Unix, Windows and embedded operating systems. A significant part of my management duties involved mentoring bachelors to doctorate level software engineers. From October 1996 to April 1998 (1 year 7 months) Postdoctoral Researcher @ University of Washington The focus of this work is developing statistically rigorous methods for the analysis of data collected using a novel survey sampling method (Respondent-Driven Sampling or RDS). This is grant funded work much of which extends the results of my statistics dissertation. Specifically I am developing improved estimation and inferential methods and developing publicly available software as a means of disseminating these methods. As part of my work I am also an active participant in the Networks Research group at the University of Washington. I also maintain active collaborations with field researchers using RDS at the University of Washington, Duke University and the Yale School of Public Health. I was the primary author of the NSF grant proposal that funds my work on this project. From March 2009 to May 2010 (1 year 3 months) National Institute of Child Health & Human Development Trainee @ Center for Demography and Ecology, University of Wisconsin-Madison As a NICHD trainee working with the Center for Demography and Ecology (CDE) I began my dissertation research on sampling hard-to-reach populations and statistical techniques to study social networks. During Fall Semester 2006, I helped to coordinate and presented materials to a joint Statistics & Social Sciences workshop series on sampling hard-to-reach populations. In addition to research activities I serve as a statistical consulting resource to faculty and graduate students in CDE. My consulting duties include helping CDE members design and carry out statistical analyses and providing a series of short courses on using the R statistical environment. From September 2006 to August 2008 (2 years) Staff Data Scientist - Simulation / Self Driving Vehicles @ Uber I've joined Uber's Advanced Technology Group to work with an amazing team to make safe autonomous vehicles a reality. We work on establishing safety through simulation, track testing, and real world testing. My role is to work directly on simulation to establish safety measures for autonomous vehicles and to serve as data science practice lead for ATG more broadly. From February 2019 to December 2019 (11 months) San Francisco Bay AreaPrincipal Data Scientist @ Salesforce I worked on developing novel data science techniques for search logs within Salesforce's search cloud, including building models for inferring search intent, and moving analytics functions from ad-hoc Splunk queries to production deployable Python software. From January 2018 to February 2019 (1 year 2 months) San Francisco, California


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In a nutshell

William Whipple Neely's Personality Type

Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

1 year(s), 10 month(s)

William Whipple Neely's Willingness to Change Jobs

Unlikely

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William Whipple Neely's Social Media Links

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