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Building and maintaining ETL pipelines with large data sets using services such as AWS Glue, EMR, Kinesis or Kafka, CloudWatch; Python development experience with proficiency in Spark or PySpark and in using API; AWS Services such as AWS Lambda, Event Bridge, Step functions, SNS, SQS, S3 and MI models; Knowledge of machine learning, deep learning AMIs and natural language processing (NLP) techniques.
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ML | AI | Machine Learning | DevOps | Data & Analytics | Infrastructure | CI/CD | Terraform | Gitlab | Azure Devops | AWS | Azure | DataBricks | Ansible | Apache Spark | Kafka | Kubernetes | Docker | Linux.
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Specialization: Machine Learning/Data Science. 90% Machine Learning / Data Science. Bachelor's, Master's degree, or Ph. D. in a relevant field: Statistics, Applied Mathematics, Operations Research, Computational Physics, Computer Science, Engineering, etc.
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Expertise using statistical analysis, machine learning algorithms, deep learning, large language models, NLP, image recognition and predictive modeling. Expertise with cloud-based machine learning platforms such as AWS SageMaker, Azure ML, or GCP AI Platform.
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Associate's or Bachelor's degree in computer science, computer information systems, computer information technology, computer engineering, or computer-based information systems, instructional technology, or business/computer related field (e.g., computer management, decision engineering, data processing.
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Our services include: natural gas gathering, treating, processing, transportation and storage; NGL transportation, fractionation, storage and import and export terminals; crude oil gathering, transportation, storage and terminals; petrochemical and refined products transportation, storage and terminals; and a marine transportation business that operates primarily on the United States inland and Intracoastal Waterway systems.
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Enterprise Products Partners L.P. is one of the largest publicly traded partnerships and a leading North American provider of midstream energy services to producers and consumers of natural gas, NGLs, crude oil, refined products and petrochemicals.
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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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A Bachelors or Masters in Computer Science, Statistics, Mathematics, Data Analysis, Machine Learning or a related field. At least 3 years of experience in data science, with a focus on data analysis and machine learning model development, or data monitoring system implementation.
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Pursuing a major in Environmental Science, Natural Resources sciences, Environmental Resource Management, Natural Resource Management, Wildlife Biology/Wildlife Studies, Fishery or Forestry, Ecology, Geology, Historic Preservation, Anthropology, Archaeology, Environmental Planning.
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The Sr. Back Office Analyst will be responsible for a variety of activities related to physical and financial natural gas trading, including settlement of natural gas commodity invoices, natural gas pipeline and exchange statements, payment processing, reconciliations, trade confirmations, and reconciliation of data to ETRM system.
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5-10 years meat and/or seafood industry (as appropriate) FSQA Management experience at a federal CFIA/FDA meat and/or seafood processing plant (as appropriate) acceptable instead of a degree. A minimum of three to five years FSQA management with additional R&D(research and development) or production-operations in a meat and/or seafood processing environment being ideal (combined experience preferred.
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Strong communication, interpersonal and collaboration skills essential Ability to manage projects with a strong focus on delivery and results Education, Training & Certifications 10 or more years of experience in the Oil/Gas industry, preferably within salt basins (Gulf of Mexico preferred) Extensive experience in Deepwater Exploration MSc or PhD of Science in a Geoscience field required Competencies The Hess Way of Working refers to competencies considered absolute pre-requisites for success.
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The JETS Space Environments team is seeking a Space Environments Engineer to provide systems engineering and multidisciplinary technical analysis/modeling support to the different NASA JSC programs.
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Generative AI: Leverage Databricks to develop and deploy innovative generative AI solutions, such as natural language processing and image generation. Knowledge of machine learning and deep learning algorithms.
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