Kyle Payne

Kyle Payne Email and Phone Number

Senior Data Scientist at YouTube @ Google
Mountain View, CA
Kyle Payne's Location
Chicago, Illinois, United States, United States
About Kyle Payne

Kyle Payne is a Senior Data Scientist at YouTube at Google. He possess expertise in r, microsoft excel, statistical modeling, data analysis, powerpoint and 26 more skills. Colleagues describe him as "While sitting next me during our State Farm internship, Kyle taught me real analysis and measure theory. Few students in our program ever push themselves this far; our graduate program focused primarily on applied topics, like the mechanics of data analysis. Fewer take the initiative to share that passion with others. But Kyle did. Over the span of several weeks, Kyle explained how Riemann integrals led to the ideas of Lebesgue. He walked me through the definition of a measure, and he even took the time to make sure I saw how all of this eventually led back to our work in probability and statistics. I know that this was especially challenging material to try and learn, and I understand that it wasn't necessarily easy to break away from work to spend this much time discussing fundamental Math. For that, I'll always be grateful. Kyle cares deeply about very difficult ideas. He has the curiosity and ambition to tackle problems from a variety of perspectives, and he has the determination to follow ideas to their conclusion. He doesn't shy away from a challenge, and he welcomes the opportunity to push himself far past limits set by his peers. He's a generalist and excels in a variety of research settings. And most of all, he's a good friend that always quick to laugh. I'm certain that Kyle has a bright research career ahead of him, either in industry or academia. And I'm jealous of all the people that will get to work with him in the future. I'm sure they'll love the experience."

Kyle Payne's Current Company Details
Google

Google

View
Senior Data Scientist at YouTube
Mountain View, CA
Website:
google.com
Employees:
1
Company phone:
916.253.7820
Kyle Payne Work Experience Details
  • Google
    Senior Data Scientist
    Google Oct 2016 - Present
    Mountain View, Ca, Us
  • Nielsen
    Data Scientist
    Nielsen May 2016 - Oct 2016
    New York, Ny, Us
    As a data scientist at Nielsen, I have:- built really interesting tools for analyzing, modeling, and processing consumer data in Python using the Python data science stack (Pandas/Numpy/Scipy/scikit-learn).- trained Statisticians in the Python/R data science stack (Pandas, Scikit-learn, statsmodels, ggplot)- worked on machine learning models for determining spatial location of consumer measurement device within a house.
  • University Of Illinois At Urbana-Champaign
    Graduate Teaching Assistant
    University Of Illinois At Urbana-Champaign Aug 2015 - May 2016
    Champaign, Il, Us
    I teach CPSC/NRES 440, An intro to statistics course for environmental scientists! Check out some of my teaching materials here: http://bit.ly/1LbTXxL
  • Dow Agrosciences
    Bioinformatics Intern
    Dow Agrosciences May 2015 - Dec 2015
    Indianapolis, In, Us
    I worked on a variety of problems including:- High-Dimensional Classification of agronomic phenotypes with expression data.- Genomic Ontology- Nuclease Classification and Detection
  • State Farm
    Magnet Intern
    State Farm May 2014 - May 2015
    Bloomington, Illinois, Us
    As a MAGNet Intern at the State Farm Research and Development Center, I am responsible for working with a project leader on a real business problem for State Farm. These projects have ranged from theoretical to underwriting applications. Some of the work includes: *Examining the use of Multinomial GLM for ternary classification *Sentiment Analysis on unstructured social media data *Loss-ratio modeling for underwriting/risk management projects *Bias correction of text data using bayes/measure-theoretic optimal rules
  • Statistics In The Community
    Statistical Consultant
    Statistics In The Community Jan 2014 - Feb 2015
    Pro-Bono Statistical Consulting for Non-Profits and governmental organizations.
  • University Of Illinois At Urbana-Champaign
    Undergraduate Research Assistant
    University Of Illinois At Urbana-Champaign May 2013 - May 2014
    Champaign, Il, Us
    The research I am currently working on is based off of the diffusion model of Ratcliff (see http://star.psy.ohio-state.edu/coglab/). The diffusion model is a novel and theoretical sound way to estimate reaction times to two-choice decision processes. For example, consider working on a true/false portion of a test, where you to want to get the answers correct (why else would you be taking a test?) while you're put underneath a time constraint - i.e. you need to finish the test in time. Under these conditions, one could imagine that how much time you might take to reach a conclusion could be proportional to how difficult a question is. Thus we can view the accumulation of reasoning that you might take until you reach a decision to effect your reaction time to answering a question; And you could visualize the "path" of reasoning that you may have to be straight - i.e. the answer is obvious to you, or the "path" may be winding, which may be when the answer is not obvious. All of this intuition basically leads to the diffusion model, which is an analytic model that measures how your cognitive processes in decision making is related to your reaction time. In technical terms, the diffusion model is based off of Markov Chains (each iteration represents a decision making process), where the state is indexed by time, (this is essentially a stochastic process). The steady state for each chain is a decision (either correct or error). The diffusion model reflects both reaction time and accuracy, and therefore is very flexible plenty of data types. Some of my interest stems from this, and the fitting/estimation procedure for the diffusion model.
  • Krannert Center For The Performing Arts
    Supervisor
    Krannert Center For The Performing Arts Aug 2012 - May 2013
  • Parkland College
    Technical Specialist
    Parkland College May 2011 - Aug 2012
    Champaign, Il, Us

Kyle Payne Skills

R Microsoft Excel Statistical Modeling Data Analysis Powerpoint Research Microsoft Office Microsoft Word Customer Service C++ Java Sas Python Statistics Photoshop Social Media Teamwork Public Speaking Categorical Data Analysis Matlab Leadership Management Analytics Programming Data Science Quantitative Research Big Data Sql Spss Machine Learning Qualitative Research

Kyle Payne Education Details

  • University Of Illinois Urbana-Champaign
    University Of Illinois Urbana-Champaign
    Statistics
  • University Of Illinois Urbana-Champaign
    University Of Illinois Urbana-Champaign
    Bachelor'S Degree

Frequently Asked Questions about Kyle Payne

What company does Kyle Payne work for?

Kyle Payne works for Google

What is Kyle Payne's role at the current company?

Kyle Payne's current role is Senior Data Scientist at YouTube.

What is Kyle Payne's email address?

Kyle Payne's email address is ky****@****ail.com

What is Kyle Payne's direct phone number?

Kyle Payne's direct phone number is +121733*****

What schools did Kyle Payne attend?

Kyle Payne attended University Of Illinois Urbana-Champaign, University Of Illinois Urbana-Champaign.

What are some of Kyle Payne's interests?

Kyle Payne has interest in Poverty Alleviation, Amateur Boxing, Muay Thai.

What skills is Kyle Payne known for?

Kyle Payne has skills like R, Microsoft Excel, Statistical Modeling, Data Analysis, Powerpoint, Research, Microsoft Office, Microsoft Word, Customer Service, C++, Java, Sas.

Who are Kyle Payne's colleagues?

Kyle Payne's colleagues are Anna Smith, Kathleen Phu, Jett Lewis, Enkoodabooaoo Cha'akmongwi, Vinita Chhetri, Marlon Bustamante, Mohamed Araby.

Free Chrome Extension

Find emails, phones & company data instantly

Find verified emails from LinkedIn profiles
Get direct phone numbers & mobile contacts
Access company data & employee information
Works directly on LinkedIn - no copy/paste needed
Get Chrome Extension - Free

Aero Online

Your AI prospecting assistant

Download 750 million emails and 100 million phone numbers

Access emails and phone numbers of over 750 million business users. Instantly download verified profiles using 20+ filters, including location, job title, company, function, and industry.