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Tyler S Byers, 419602 167Th Ave SE, Snohomish, WA 98290

Related to:
Jennifer E Arlt 59 Patricia A Butterfield 56 John R Byers 92

Tyler Byers Phones & Addresses

Snohomish, WA   

Spokane, WA   

Mukilteo, WA   

Everett, WA   

Fayetteville, NC   

Work

Company: The boeing company Oct 2013 Position: Methods process analyst

Education

School / High School: University of Washington Bothell School of Business Bothell- Bothell, WA 2013 Specialities: Bachelor of Business Administration in Technology and Innovation Management, Management

Skills

Detailed Data Analysis • Project Management • Process Improvement • Team Building • Leadership • Facilitation • Mediation & Advocacy • Project Leadership • Customer Focused • Coaching and Mentoring • Training & Development • Performance Management • Organizational Development • Highly Adaptable
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Tyler Byers resumes & CV records

Resumes

Tyler Byers Photo 37

Lead Data Scientist

Location:
2503 south Viewmont Dr, Greenacres, WA 99016
Industry:
Information Services
Work:
Risklens Feb 2018 - Jan 2019
Senior Data Scientist Risklens Feb 2018 - Jan 2019
Lead Data Scientist Headsup Weather Inc May 2017 - Feb 2018
Data Scientist Itron Jun 2017 - Feb 2018
Data Scientist Itron May 2015 - Jun 2017
Machine Learning Software Developer Federal Government Jun 2013 - May 2015
Team Lead -- Data Acquisitions Federal Government Nov 2005 - Jun 2013
Engineering Data Analyst Us Paralympics 2003 - 2008
Paralympian - Athletics Ibm May 2005 - Nov 2005
Software Engineer The University of Arizona Jul 2004 - Nov 2005
Adaptive Athletics Coach Ibm May 2003 - May 2005
Co-Op Pre-Professional Programmer The University of Arizona Jan 2003 - May 2003
Teaching Assistant Department of the Interior May 2002 - Aug 2002
Math and Computer Science Intern: Office Automation Clerk and Gs-4 Relion May 2001 - Aug 2001
Engineering Intern
Education:
Regis University 2016 - 2021
Master of Science, Masters, Data Science Udacity 2018 - 2018
Udacity 2017 - 2017
Edx 2016 - 2016
Udacity 2013 - 2015
University of Washington 2015 - 2015
The Johns Hopkins University 2014 - 2015
University of Arizona 2000 - 2005
Bachelors, Bachelor of Science, Mathematics, Engineering Joel E. Ferris High School 1996 - 2000
Skills:
R, Python, Data Analysis, Machine Learning, Data Science, Statistics, Leadership, Matlab, Sql, Linux, Management, Html, Unix, Hadoop, Data Mining, Mapreduce, Communication Skills, Pattern Recognition, Data Modeling, Analytics, Software Development, Aerospace, Briefing, Trend Analysis, Mathematical Modeling, Forecasting, Data Visualization, Jekyll, Satellite Tool Kit, Xmidas, Numerical Analysis, Mongodb, Apache Spark, Time Series Analysis, Programming, Writing, Mathematics, Clean Energy Technologies, R Packages, Microsoft Azure, Consulting, Deep Learning, Xgboost, Tensorflow, Keras, Artificial Intelligence, Cyber Security, Python
Interests:
2008 Paralympian
Wheelchair Racing
Traveling
Language
Self Study
Snow Skiing
Triathlons
Was 2004
Languages:
English
French
Certifications:
Data Science Specialization
Data Science and Engineering With Spark Xseries Certificate
Big Data Xseries Certificate
Intro To Hadoop and Mapreduce
Exploratory Data Analysis
Introduction To Data Science
Intro To Artificial Intelligence
Intro To Computer Science
Intro To Statistics
The Data Scientist’s Toolbox
Getting and Cleaning Data
R Programming
Reproducible Research
Statistical Inference
Regression Models
Practical Machine Learning
Developing Data Products
Data Science Capstone
Machine Learning
Data Wrangling With Mongodb
Intro To Machine Learning
The Analytics Edge
Introduction To Big Data With Apache Spark
Scalable Machine Learning (Apache Spark)
Introduction To Genomic Technologies
Machine Learning Foundations: A Case Study Approach By University of Washington
Machine Learning: Regression By University of Washington
Machine Learning: Classification By University of Washington
Introduction To Apache Spark
Machine Learning: Clustering & Retrieval By University of Washington
Distributed Machine Learning With Apache Spark
Big Data Analysis With Apache Spark
The R Programming Environment
Advanced R Programming
Building R Packages
Building Data Visualization Tools
Machine Learning Specialization By University of Washington
Mastering Software Development In R Capstone
Mastering Software Development In R Specialization
Microsoft Dat202.3X: Implementing Predictive Analytics With Spark In Azure Hdinsight
Neural Networks and Deep Learning
Structuring Machine Learning Projects
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Convolutional Neural Networks
Usable Security
Introduction To Cyber Attacks
Real-Time Cyber Threat Detection and Mitigation
Cyber Attack Countermeasures
Enterprise and Infrastructure Security
Sequence Models
Deep Learning Specialization
Artificial Intelligence Nanodegree
Tyler Byers Photo 38

Tyler Byers

Tyler Byers Photo 39

Tyler Byers

Tyler Byers Photo 40

Tyler Byers

Tyler Byers Photo 41

Tyler Byers - Mukilteo, WA

Work:
The Boeing Company Oct 2013 to 2000
Methods Process Analyst Panasonic Avionics Corporation Feb 2013 to Jun 2013
Human Resources Intern Everett Vet Center Dec 2009 to Jun 2013
Work Study Employee U.S. Army Feb 2005 to Jul 2009
Airborne Infantry Squad Leader
Education:
University of Washington Bothell School of Business Bothell - Bothell, WA 2013
Bachelor of Business Administration in Technology and Innovation Management, Management
Skills:
Detailed Data Analysis, Project Management, Process Improvement, Team Building, Leadership, Facilitation, Mediation & Advocacy, Project Leadership, Customer Focused, Coaching and Mentoring, Training & Development, Performance Management, Organizational Development, Highly Adaptable

Publications & IP owners

Us Patents

Electric Vehicle Distributed Energy Resource Management

US Patent:
2023004, Feb 9, 2023
Filed:
Jun 28, 2022
Appl. No.:
17/851565
Inventors:
- Liberty Lake WA, US
Tyler Byers - Liberty Lake WA, US
Michael Ting - Oakland CA, US
International Classification:
B60L 53/62
G07C 5/00
G05B 13/04
Abstract:
A method and system for managing electric vehicle (EV) distributed energy resource(s) (DER) are disclosed. A DER analytics engine may receive electricity consumption data of a plurality of sites from corresponding electricity meters of the plurality of sites, detect EV charging information based at least in part on the electricity consumption data, obtain EV telematics data of EVs associated with the EV charging information, reconcile the EV charging information and the EV telematics data, and generate, based on the reconciled EV charging information and the EV telematics data, models for at least one of continuous EV load prediction, electrical vehicle supply equipment (EVSE detection), and/or optimization for at least one of aggregated load, load per feeder, or maximum revenue for time-of-use tiers.

Possible Relatives

Cynthia L Byers  David J Byers  Dawn R Byers  Deanna L Byers  Dale Byers  Damion D Byers  Deborah A Byers  Tyler R Johnson  Tyler C Johnston  Tyler D Stanfield 

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