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Leverages technical proficiency of big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development.
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Demonstrated experience using big data processing tools such as Apache Spark or Trino. Create data science and data engineering products that include data models, data ingestion/transform, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g., file output, database output, standard/streaming output) or a user interface or dashboard.
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Demonstrated experience implementing machine learning models on text and multimedia data such as Spark NLP and Computer Vision models. Demonstrated experience with Apache Spark and managing Spark clusters.
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Demonstrated experience tuning and optimizing Apache Spark. Demonstrated experience using artificial intelligence and machine learning technologies/packages. Demonstrated experience developing machine learning models on text data and structured datasets.
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Demonstrated experience with Linux operating systems and shell scripting such as Bash. Demonstrated experience developing machine learning models on text data and structured datasets. Demonstrated experience with the DataBricks platform and DataBricks API & CLI. Demonstrated experience understanding Hadoop Distributed File System (HDFS.
$122,200 - $220,900 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Demonstrated experience with data-oriented workflow orchestration tools within the Azure ecosystem, such as Azure Data Factory or Azure Logic Apps, or external tools like Apache Airflow, ML flow, or Argo, required.
$90,000 - $115,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Stay current with emerging trends and technologies in big data and cloud computing, particularly related to Databricks and Apache Spark. Experience with Apache Spark and related technologies.
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Experience with machine learning and data science workflows on Databricks. Experience with machine learning and data science workflows on Databricks. Implement best practices for data governance, security, and compliance on the Databricks platform.
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The Contractor Team shall create data science and data engineering products that include data models, data ingestion/transform, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g. file output, database output, standard/streaming output) or a user interface or dashboard.
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Develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices. Demonstrated experience using data engineering tools such as Apache Nifi to preprocess, modify, aggregate, load, index, and archive large data collections.
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Our client seeks a Machine Learning Engineer to provide data science and data engineering services, including developing data models, data ingestion/transformation, analytics, and machine learning.
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Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr, Kibana, neo4J, MariaDB, Postgres, Docker, Puppet, and many others. , Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.
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The Software Engineering Senior Associate, Valuation & Capital Market Analysis – Complex Financial Instruments will be a member of the Data Science team that builds Python based models and related infrastructure to speed up the development and deployment of machine language (ML), statistical and mathematical models at scale and bring game-changing impact to our client’s decisioning.
$90,000 - $115,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Demonstrated experience with Databricks and Apache Spark. The Contractor shall identify and leverage datasets relevant to the question area, and produce actionable insights through data exploration, analysis, visualization, and the application of statistical and machine learning techniques.
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