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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake, Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). Sia Partners is looking for a talented Data Engineer to support our activities within the Data Science Business Unit. You will be working alongside with our Data Science consultants and our clients on Data Engineering topics, including creating relevant data models, developing powerful data pipelines, exposing them through various mechanisms including APIs, and using data visualization tools to efficiently present data.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Plus, to be a Committer or PMC Member with the Apache Software Foundation on big data technologies: Apache Spark, Hadoop Stack, Kafka, Comet, Atlas, delta. Recognized Subject-Matter Expert big data engineering and cloud-based data warehouse.
$154,000 - $278,800 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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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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Proficiency in DevOps and automation technologies, such as Jenkins, Docker, Terraform, Ansible, Apache Air Flow. Familiarity with big data tools like Cassandra, Hadoop, Plotly, Storm, BigQuery.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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The solutions developed draw on IT-RI’s strong capabilities in statistical modeling, machine learning, natural language processing, information retrieval, statistical genomics, data mining, and big data management and analytics.
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Research in Computational Data Science and Engineering includes: big data and computational statistics, AI and Machine Learning, internet of things, large and complex systems, intelligent transportation and infrastructure systems, remote sensing, autonomous vehicles, virtual and augmented reality, e-commerce, image and video processing, scientific and interactive visualization, high-performance computing, scalable algorithms, bioinformatics, and multi-scale multi-physics engineering systems.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Some exposure to Big Data technologies, Apache Spark, AWS, AWS S3, amazon Glue, cloud -based data architecture is preferred. Qualifications Bachelor’s degree in computer science, Data Science, or data engineering 3-5 years of experience as a Data Analyst with exposure to data governance practices.
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Qualifications Job Qualifications: • Expertise in advanced data science, machine learning, and artificial intelligence techniques, supported by a strong track record in programming languages such as Python, R, SQL, and proven software engineering methodologies.
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As a Data Science intern on our team, you’ll be working on various algorithms and using Natural Language Processing (NLP) methods to work on some of our most interesting problems using expertly curated datasets.
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Job Description: The big data architect will support the development of autonomous driving software solutions by playing the role of subject matter expert for the big data systems, underlying data and data products.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Preferred Qualifications:Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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big data science jobs Company: Careerbuilder
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