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Expertise in data modeling, predictive and prescriptive analytics techniques, machine learning, and SQL query optimization; strong understanding of data governance, data quality, and data security principles.
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Experience with Spark jobs for data processing, analysis, and machine learning tasks using Databricks. Develop and optimize Spark jobs for data processing, analysis, and machine learning tasks.
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Strong understanding of machine learning, statistical analysis, and predictive modeling. Develop predictive models and machine-learning algorithms to solve complex problems.
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Databricks Platform Utilization: Utilize the full capabilities of the Databricks platform for data processing, ETL, analytics, and machine learning. Strong knowledge of database technologies, ETL processes, cloud platforms, and big data technologies.
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In-depth knowledge of advanced analytical techniques, such as machine learning, natural language processing (NLP) and applied statistics. Knowledge of tools such as Python, R, SQL, Data Modeling, ETL, JSON, XML, Oracle Dashboards, Tableau, Visual Basic and Microsoft Access.
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Knowledge of other emerging technologies such as artificial intelligence, machine learning, or natural language processing in the context of content management. Hands-on experience with ETL tools such as AWS Glue, Informatica and integration platforms such as Mulesoft or webMethods are good to have.
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As a Senior Reliability Engineer, you will play a critical role in ensuring the robustness, availability, and performance of our cutting-edge Data Engineering and Machine Learning Platforms.
$82,000 - $185,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Data Science, Machine Learning, and/or Deep Learning experience. Utilize Machine Learning and Data Engineering techniques to support new product offerings and drive thought leadership in the technology and financial marketplaces.
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NET development, MS Office Groups, Azure Machine Learning, Microsoft Flow, Power Automate, Kingswaysoft, Logic Apps, enterprise ETL and 3rd Party / ISV product experience preferred.
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Proficiency in SQL, Python, R, or other programming languages commonly used in data analysis and machine learning. Strong understanding of AI concepts, machine learning, and their practical applications in the oil and gas industry.
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Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machine-learning, and deep learning. Demonstrated experience applying deep learning and machine learning processing libraries, including PyTorch, TensorFlow, Keras, and scikit.
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Experience in several of the following areas: database architecture, ETL, business intelligence, big data, machine learning, advanced analytics. To continue this transformation, we're seeking an experienced Amazon Web Services (AWS) cloud engineer who has expertise in the strategy, design, development, and implementation of large-scale projects in the cloud.
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We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more.
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Assigned as the SRE expert to the Data Engineering Team. The data team manages all aspects of our data strategy, analysis, engineering, and machine learning. Stay current with technology trends and developments in the industry Big Data Ecosystem like Cloudera( CDP/CDH) and ETL Application monitoring knowledge.
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Data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics; and support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses.
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