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Leverage data science frameworks like TensorFlow, PyTorch, and Spark ML to build robust and scalable machine learning solutions. Join the Anheuser-Busch NAZ Tech Data and Analytics Team as a Machine Learning Engineer.
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Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Doctorate, Masters: Artificial Intelligence.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Expertise in NLP and machine learning frameworks (e.g., TensorFlow, PyTorch). Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.
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The Data Science team at Meijer leads the strategy, development and integration of Machine Learning and Artificial Intelligence at Meijer. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
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Our core offerings Bidder-as-a-Service (BaaS) and the Beeswax DSP provide clients with agility, custom optimizations, and extensible APIs. We are looking for a Machine Learning Engineering with an in-depth working knowledge of the latest in Machine Learning/Data Science technologies and cloud platforms to join our Optimization team, which have three defining pillars: machine learning, software engineering, and machine learning operations (MLOps.
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The ideal candidate will have a strong background in data science, programming, and machine learning algorithms and will be passionate about leveraging data to drive business decisions.
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Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Conducting experiments on state-of-the-art machine learning models using Tensorflow for real world, large scale problems. Conducting experiments on state-of-the-art machine learning models using Tensorflow for real world, large scale problems.
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Bachelor's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines and 5 or more years experience in predictive analytics or equivalent.
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In this role, you will collaborate with researchers to develop machine learning methods for computational biology and drive the implementation and testing of novel research ideas using cutting-edge deep learning techniques.
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Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
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Additionally, we are dedicated to crafting exceptional data infrastructure and innovative solutions in the realms of data science and machine learning. Stay up-to-date with the latest advancements and trends in machine learning and data science and apply them to evolve the measurement system.
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Scientific background in life sciences or engineering and demonstrated expertise in one or more of the following areas: data analytics, data visualization, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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