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As a member of the Data Engineering team, the Machine Learning Engineer will work closely with business domain experts and data scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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The Data Scientist role on the Marketing Optimization Analytics team is responsible for building end-to-end Machine Learning based Analytic Data Products that will directly impact short-term and long-term marketing strategy.
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DE identifying key trends and customer behaviors that influence business decisions by building hypothesis for mining digital or live channel data in AWS and Snowflake EDL, using SQL, Python, Elasticsearch and Amazon Web Services (AWS) technologies Athena, Glue, Sage maker, Kibana, S3, Quicksight, and API Gateway.
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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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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. 7+ years of experience in at least one of the following: JavaScript, Java, TypeScript, SQL, Python, or Go.
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Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
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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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Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Do you love building and pioneering in the technology space.
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Experience building and designing data and analytics on enterprise solutions such as Azure - Data Factory, Log Analytics, Databricks, Synapse, Power BI, ADLS Gen2, Polybase and Machine Learning/AI.
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5+ years of experience as a Machine Learning engineer building production-level pre/post-processing data pipelines for ML/DL modelExperience in statistical analysis & visualization on datasets using SQL, Pandas or R.
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Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning. Using tools such as SQL, DataBricks, Talend, Python, Microsoft Power Platform and Azure Data Factory.
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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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Collaborate with data science and data engineering team to build scalable and reproducible machine learning pipelines for training and inference. 4+ years of experience in working with Python, SQL, PySpark and bash scripts.
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In this role, you will leverage your expertise in Python, Natural Language Processing (NLP) techniques, algorithms and statistics, as well as your familiarity with US Department of Defense mission needs, to deploy, optimize, and evaluate innovative machine learning and algorithmic solutions in client environments.
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Proficiency in analytic tools such as Python, R, SQL, Tableau, SAS, AWS, Microsoft Azure, Machine Learning Algorithms, Deep Learning, NLP, and Data Visualization, with the ability to adapt to new technologies quickly.
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team building services machine learning python sql jobs Company: Capital One Financial Corporation
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