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Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka. 8+ years of experience in developing business applications for Machine Learning and Data Science workloads.
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Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm.
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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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More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
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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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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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Expertise in Cloudera Big Data Technologies, including Cloudera Distribution of Hadoop (CDP), Apache Hadoop, Apache Spark, Apache Hive, Apache Impala, and Apache HBase, with hands-on experience in deploying, configuring, and optimizing these technologies for large-scale data processing and analytics.
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Experience with machine learning and AI-driven data processing. -Proficiency in data engineering tools and technologies such as Apache Airflow, Spark, Kafka, Hadoop, or similar.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Collaborate with cross-functional teams including data scientists and product managers to align machine learning solutions with business objectives.
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Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Design and build robust, scalable solutions and data pipelines to automate the ingestion, processing and delivery of all types of data: structured and unstructured, batch, and real-time streaming data.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
$275,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Frameworks & Tools: Extensive experience with Hibernate/JPA, AWS, Databricks, Angular/React JS, and JBOSS Enterprise SOA. Knowledge of Apache Kafka, Apache Spark, and ActiveMQ is a plus.
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What you'll do:- Design, build, and manage data pipelines using Apache Spark and Scala. We also use cross-departmental data and machine learning to build a holistic view of true profitability, saving millions of dollars across item categories and geographies while assisting our leadership in making better decisions faster.
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Familiarity with JavaScript libraries such as Lodash, Math.js, Moment, Numeral, and es6-shim preferredProficiency with server-side languages for structured data processing; Python, PySpark, Java, Apache Spark, and SparkSQL preferred.
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machine learning apache spark data processing jobs Title: engineer Company: Newsbreak
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