Jeremy Betz
Data Scientist at Dinamico Systems- Claim this Profile
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English Native or bilingual proficiency
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German Professional working proficiency
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French Elementary proficiency
Topline Score
Bio
LinkedIn User
Jeremy has mad mathematical skills. He solves the hardest probability problems as if they were toy puzzles. His Python game is on point too. He is also worldly and manages to be up to date on all the recent developments in tech, music, games, and global good. It’s nicely reflected in his portfolio of Metis projects: supervised classification of water wells in Africa, analysis of soccer player characteristics and their impact on the game result; polarity and subjectivity analysis of tweets by political analysts; and the jewel of the crown, his final project where he trained a neural net model to predict opponent’s card in real time in the game of Hearthstone. He is sharp, independent, with great ability to get to the core of the problem fast, cutting through the fluff. Jeremy speaks fluent German and teaches kids soccer. Any company that is hiring for data scientists should be checking on Jeremy’s availability.
LinkedIn User
Jeremy has mad mathematical skills. He solves the hardest probability problems as if they were toy puzzles. His Python game is on point too. He is also worldly and manages to be up to date on all the recent developments in tech, music, games, and global good. It’s nicely reflected in his portfolio of Metis projects: supervised classification of water wells in Africa, analysis of soccer player characteristics and their impact on the game result; polarity and subjectivity analysis of tweets by political analysts; and the jewel of the crown, his final project where he trained a neural net model to predict opponent’s card in real time in the game of Hearthstone. He is sharp, independent, with great ability to get to the core of the problem fast, cutting through the fluff. Jeremy speaks fluent German and teaches kids soccer. Any company that is hiring for data scientists should be checking on Jeremy’s availability.
LinkedIn User
Jeremy has mad mathematical skills. He solves the hardest probability problems as if they were toy puzzles. His Python game is on point too. He is also worldly and manages to be up to date on all the recent developments in tech, music, games, and global good. It’s nicely reflected in his portfolio of Metis projects: supervised classification of water wells in Africa, analysis of soccer player characteristics and their impact on the game result; polarity and subjectivity analysis of tweets by political analysts; and the jewel of the crown, his final project where he trained a neural net model to predict opponent’s card in real time in the game of Hearthstone. He is sharp, independent, with great ability to get to the core of the problem fast, cutting through the fluff. Jeremy speaks fluent German and teaches kids soccer. Any company that is hiring for data scientists should be checking on Jeremy’s availability.
LinkedIn User
Jeremy has mad mathematical skills. He solves the hardest probability problems as if they were toy puzzles. His Python game is on point too. He is also worldly and manages to be up to date on all the recent developments in tech, music, games, and global good. It’s nicely reflected in his portfolio of Metis projects: supervised classification of water wells in Africa, analysis of soccer player characteristics and their impact on the game result; polarity and subjectivity analysis of tweets by political analysts; and the jewel of the crown, his final project where he trained a neural net model to predict opponent’s card in real time in the game of Hearthstone. He is sharp, independent, with great ability to get to the core of the problem fast, cutting through the fluff. Jeremy speaks fluent German and teaches kids soccer. Any company that is hiring for data scientists should be checking on Jeremy’s availability.
Credentials
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Exam FM - Financial Mathematics
Society of ActuariesAug, 2013- Nov, 2024 -
Exam P - Probabity
Society of ActuariesJan, 2013- Nov, 2024
Experience
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Dinamico
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United States
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Business Consulting and Services
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1 - 100 Employee
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Data Scientist
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Aug 2019 - Present
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U.S. Soccer Federation
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United States
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Spectator Sports
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700 & Above Employee
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U.S. Soccer Hackathon Finalist
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Jun 2018 - Jun 2018
Created finalist project in Official U.S. Soccer Hackathon involving the Implementation of k-means clustering of players into squad roles using Opta positional data in order to Demonstrate differences in roster spot value across positional groups Created finalist project in Official U.S. Soccer Hackathon involving the Implementation of k-means clustering of players into squad roles using Opta positional data in order to Demonstrate differences in roster spot value across positional groups
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Metis
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United States
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Higher Education
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1 - 100 Employee
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Data Scientist
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Apr 2017 - Jul 2017
Metis is Data Science bootcamp that teaches machine learning, statistics, programming, data visualization, and design through a project based curriculum. In three months, I completed five data science projects from data acquisition to presentation including data cleaning, exploratory analysis, supervised and unsupervised machine learning, natural language processing, and web app development. Projects were as follows: 1.) Developed a node.js app to generate real time predictions of opponent’s future cards in Hearthstone using a 2 layer « card2vec » neural network trained on previous card sequences attained from the Track-o-Bot API 2.) Produced an NLP topic model of 6 million tweets from popular political journalists and bloggers using latent dirichlet allocation and latent semantic indexing, applied word2vec sentiment analysis to each user, and clustered users by sentiment with a k-means algorithm 3.) Analyzed geographic and water quality features of water sources in Tanzania to classify functional status using a random forest classifier implementing a Naive Bayes model to impute missing feature values to correctly classify the functional status of 80% of sources 4.) Developed a codependent expected goal difference model using linear regression of match features from WhoScored.com in order to demonstrate distinction in feature significance between home and opposition 5.) Analyzed MTA turnstile data to optimize deployment of canvasing street teams in NYC Show less
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Education
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2010 - 2015
University of Wisconsin-Madison
Bachelor of Arts (B.A.), Economics, Statistics
Community
