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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch.
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Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred. Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products.
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Experience applying data preparation methods, feature creation engineering, exploratory data analysis, model creation, and data visualization applied to advanced analytics, machine learning and artificial intelligence.
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A Bachelor’s degree from an accredited college or university in a field of applied research such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health that includes 12 semester or 18 quarter units of coursework in data science, predictive analytics, research methods or statistical analysis.
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Employer will accept a Master’s degree, or foreign equivalent, in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field.
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Deep knowledge and hands-on expertise in predictive modeling, statistical inference, machine learning, and other advanced analytical techniques. The focus of the team is to apply machine learning, predictive analysis, and data-mining techniques to develop accurate, explainable, and replicable solutions for our clients.
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R) Thorough knowledge of statistical and predictive modeling, machine learning, probability and decision theory, and other quantitative methods Experience working within SDLC and Agile development methodologies Required: Team Leadership: Leads by example; coaches in the moment; sets clear expectations and holds individuals accountable; inspires team to bring best selves; develops talent.
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Specialized experience for this position includes: Experience applying analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory; link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the study.
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Experience using statistical analysis and computing, machine learning, deep learning, processing large data sets, data visualization, data wrangling, mathematics, and programming.
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Utilizes an in-depth knowledge of data science techniques and methodologies such as machine learning, predictive analysis, prescriptive analysis and optimization, and other emerging analytical techniques to assist, consult, or lead others in the application of data science techniques.
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Identifies and/or develops innovative and effective approaches and methodologies; applies advanced operations research and data science techniques for quantitative analysis, statistical analysis, forecasting, predictive modeling, prescriptive analysis, and optimization; and validates analysis and outcomes.
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And data science techniques for quantitative analysis, statistical analysis, forecasting, predictive modeling, prescriptive analysis, and optimization; and validates analysis and outcomes.
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Learning, predictive analysis, prescriptive analysis and optimization, and other emerging. Defines and documents the specific analytics approaches applied in project delivery.
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Research, Applied Analytics and Statistics. BASIC REQUIREMENT: EDUCATION: A degree in mathematics, statistics, computer science, data science, or field directly related to the position.
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Utilizes an in-depth knowledge of data science techniques and methodologies such as machine. modeling, interpreting models, and/or reporting quantitative information, trends, relationships.
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machine learning applied mathematics predictive modeling analytics jobs in Anoka, Minnesota
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