You will deploy machine learning and data-science to simplify shopping experience for pet-parents, to maximize reach and discovery of new products of Chewy vendors and helping create a win-win ecosystem; Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy advertising solutions; You will lead new models from ideation to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications; Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling
Requirements:
An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or 10+ years’ experience designing optimization and machine learning solutions for large scale applications; Ability to understand and apply advanced mathematics and DS methodologies; Experience in building distributed pipeline, tuning, optimizing and evaluation; Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings
Text:
Staff Machine Learning Engineer You will deploy machine learning and data-science to simplify shopping experience for pet-parents, to maximize reach and discovery of new products of Chewy vendors and helping create a win-win ecosystem; Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy advertising solutions; You will lead new models from ideation to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications; Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or 10+ years’ experience designing optimization and machine learning solutions for large scale applications; Ability to understand and apply advanced mathematics and DS methodologies; Experience in building distributed pipeline, tuning, optimizing and evaluation; Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings
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