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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Looking for a Data Engineer with SQL, Python, ADF, Databricks, Kafka and ideally Snowflake experience to work 100% remote. 4+ years of enterprise data warehouse development with SQL, Python, Azure Data Factory (ADF), Azure Databricks, Kafka, and ideally Snowflake experience.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Manipulates and extracts Medicare, Medicaid, and other healthcare claims data stored in Cloud environment using appropriate software such as SAS, Snowflake, Python, R, SQL, and other software as appropriate for the task.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$184,000 - $248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Employ cutting edge Natural Language Processing (NLP) and Machine Learning (ML) techniques to solve complex natural language problems. Master’s degree or PhD in Computer Science, Electrical Engineering, Computational Linguistics, Statistics, Applied Mathematics, or similar major.
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Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively. The Data Scientist is responsible for using advanced statistical, algorithmic, machine learning, data mining and visualization techniques to help advance and complete client projects.
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Big data concepts and technologies, such as: Apache Hadoop, Apache Hive, Solr, Cloudera, MapReduce, R, Spark, Kafka, NiFi, and the ELK (ElasticSearch, Logstash, Kibana) stack.
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Acuity is looking for a Data Engineer to join our Engineering Team. In this position, you will apply your skills in data science, data analytics, and data warehousing to pioneer cloud and data services with our clients.
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Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Display analytic results in text and visually using appropriate data science, business intelligence, and visualization tools, such as Python, R, SQL, Tableau, PowerPoint, Excel, and communicate results to client audiences at all levels with presentations and briefings.
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DUTIES AND RESPONSIBILITIES Develop, implement, and support scalable data integration (ETL/ELT) processes, covering storage, ingestion, cleansing, curation, unification, presentation, using new or current technologies (Azure SQL Server, Data Factory, Salesforce, Qualtrics, Drupal, Python, Power BI, Power Apps) Develop and enhance data architecture to directly improve operational efficiency for the business, continuing to build out an enterprise-level data ecosystem.
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As a big data engineer at Booz Allen, you'll use your skills and experience to implement data engineering activities on some of the most mission-driven projects in the industry.
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