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By combining scientific engineering, cloud computing, and vast meteorological data resources, we provide crucial answers for our clients. Proficiency in programming languages used in scientific computing and data engineering/analysis, such as Python, Fortran 77/90, C/C.
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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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Experience in cloud environments with a blend of data science skills (remote sensing, physics, geospatial, imagery process, etc) and computer science understanding is a plus for this position.
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These applications leverage cloud computing, big data, mobile, data science, data warehousing, machine learning using state of the art software development applications and frameworks.
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Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). A master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 – 7 years’ experience in data science or a similar role.
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This role will be part of a dedicated hybrid actuarial/data science team designing and delivering powerful analytical tools utilizing statistical modeling, machine learning, cloud computing, and big data platforms to enhance or overhaul core actuarial processes.
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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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Proven expertise in Apache Spark, Apache Beam, and Airflow, with a deep understanding of distributed computing and data processing frameworks. Proven experience building enterprise-grade software in a cloud-native environment (GCP or AWS) using cloud services such as GCS/S3, Dataflow/Glue, Data proc/EMR, Cloud Function/Lambda, Big Query/Athena, Big Table/Dynamo.
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Strong background in cloud computing and data-Intensive applications and services, with a focus on Google Cloud Platform. Google Associate Cloud Engineer or Data Engineer certification is a plus.
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You have a proven track record coding with at least one programming language (e.g., Scala [preferred], Python)You’re experienced in one of cloud computing platforms (e.g., GCP, Azure)You’re skilled in data modeling & data migration protocols.
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Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and experience in deploying machine learning models in a cloud environment using platforms such as AWS SageMaker and GCP Vertex AI.
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Work with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. Ascend Performance Materials Holdings, Inc. in Houston, Texas seeks Data Science Manager (IT Business Manager.
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Expertise in AWS cloud data architectures (RDS, S3 Data Lakes, Snowflake, Elasticsearch, Redshift, DynamoDB, Neptune) Expertise in cloud computing (AWS), containerization (Docker and Kubernetes), and infrastructure as code (e.g. Terraform) in the Healthcare domain.
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4+ years of experience with building, operating, and maintaining compliant cloud computing environments in Amazon Web Services, Microsoft Azure, or Google Cloud Platform. As a cloud computing infrastructure architect, you know how to take advantage of cloud capabilities.
$84,600 - $193,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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This position is responsible for the strategic planning, management, and oversight of enterprise applications, data center operations, server/database infrastructure, cloud services, data storage.
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data science cloud computing jobs Title: ops engineer
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