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Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep. Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing.
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Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods. In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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3+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service. 7+ years of experience in at least one of the following: JavaScript, Java, TypeScript, SQL, Python, or Go.
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Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
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Good to have Experience in Azure cloud technologies like PySpark, Synapse, ADF, Databricks, Python, Scala and SQL. Hands-on experience in one or all the following areas: LLM, NLP, DL (Deep Learning), ML (Machine Learning), object detection/classification, tracking, etc.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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CUDA, Julia, R and/or SQL), machine learning / deep learning methods including neural network design, computer vision / image analysis, and statistical analysis. Preference is for candidates with experience with common open source scientific computing/machine learning libraries including: scipy, pandas, statsmodel, OpenCV, XGBoost, PyTorch / TensorFlow.
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Ideal candidate would have industry experience in the field of Artificial Intelligence, Machine Learning, and/or Cloud Computing. A USPTO-registered Attorney or Patent Agent with a degree in Computer Science, Computer Engineering, or a closely related field.
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Design, build, and deploy data engineering pipelines that extracts, transforms raw data into analytics base tables to support downstream machine learning models using languages such as Python, R and SQL.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. For data Science/Machine learning Positions. Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT.
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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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Data science, data analysis, statistics, or related field, Master's degree in Business, Computer Science, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field, Related industry experience (for example, retail, merchandising, healthcare, eCommerce), Successful completion of assessments in data analysis and Business Intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power BI, or Tableau.
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Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation.
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