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The GCP Data Solution Architect (SA) is a pre-sales professional, responsible for solution development in support of Data Modernization and Artificial Intelligence engagements leveraging Google Cloud in collaboration with TEKsystems sales partners.
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Experience with data processing (e.g., Spark, BigQuery, DataProc), storage (e.g., S3, Google Cloud Storage), transport (e.g., Kafka, PubSub), and orchestration (e.g., Airflow, Luigi.
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Experience in performing ETL and data engineering work by leveraging multiple google cloud components using Dataflow, Data Proc, BigQuery. Experience in building high-performing data processing frameworks leveraging Google Cloud Platform and Teradata.
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As a Data Scientist, youll use your full toolkit statistical modeling, machine learning, data mining, data visualization, and software engineering to develop data products and models that are used by millions of users and power the growth of our business.
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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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Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch). Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Research and apply emerging forms of statistical, machine learning (neural networks / deep networks, ensemble methods, natural language processing, computer vision) and engineering methods to Royal Caribbean Cruise Lines, data science and AI ecosystem.
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10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science. Cloud ecosystem experience (Azure, AWS, and/or Google) Modern Data Stack experience (Snowflake, Synpase, Databricks, Redshift, DBT, and/or Airflow.
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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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We seek a Data Engineer who brings a robust skill set and extensive experience in cloud-based data engineering experience particularly within the realm of Azure and Databricks using Python, PySpark and cloud SQL. Critical thinking and problem-solving abilities are paramount, as you will navigate evolving and complex requirements and collaborate with stakeholders across diverse technical backgrounds.
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Knowledge and proven use of contemporary data mining, cloud computing, and data management tools: Microsoft Azure, AWS Cloud, Google Cloud, Hadoop, HDFS, MapR, and Spark.
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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.
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