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The GPS AI & Data Engineering offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to advance and enable the key mission outcomes for our clients.
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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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Implement and deliver high quality DevOps solutions for our new state of the art AI model deployment and execution platform using technologies like Gitlab, ADO, Terraform to deliver services such as Databricks, Kubernetes, Postgres, Azure Data Factory, Azure Cognitive Search.
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The Data Integration Specialist partners with our client external integration teams and our internal operations and client facing teams to ensure that our product data needs are met with quality and efficiency.
$26.88 - $54.66 an hourFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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4+ years of professional experience as a data scientist in the SaaS industryWorking knowledge of Unix command-line/shell and gitExperience deploying models in a production environment, ideally with Databricks.
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The primary focus involves the migration of data landing and transformation jobs from Hadoop to Airflow (Astronomer) and BigQuery. The Data Software Engineer position will involve design, implementation, testing and launch of new applications for loading dealer data and generating analytical insights.
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We are seeking a highly experienced Senior Data Engineer with a deep understanding of PySpark using Databricks or AWS Glue or AWS EMR and cloud-based databases such as Snowflake. 5+ years of experience in data engineering, with a strong background in Apache Spark and cloud-based databases such as Snowflake.
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Sidekick is an open source ETL framework for syncing data between SaaS tools (Salesforce, Zendesk, Notion, etc) to vector stores, a necessary step in building GPT powered applications. You ideally have a background in data engineering and should be just as comfortable making architectural decisions as implementing them in code.
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Querying, algorithms, data engineering, natural language processing, engine recommendation, experimentation, programming, data storytelling and intelligence, predictive modeling, and machine learning.
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Keywords : GCP, Google Cloud Platform, BigQuery, Composer, SQL, Python, Data Engineering, Data Pipelines. Experience working with Airflow as workflow management tools and build operators to connect, extract and ingest data as needed.
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Norfolk Southern Corporation is currently seeking a Big Data Engineer with an affinity for working with others to create successful solutions. 3+ years of Big Data tools like Hadoop, Spark, Spark SQL, Kafka, Sqoop, Hive, S3, HDFS.
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Experience with modern data architectures and modern data platforms like Snowflake, Databricks etc. Experience with data technologies: Hadoop, Spark, Kafka, Spark & Kafka Streaming, Python, Scala, Talend etc.
$113,668 - $203,468 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Fox Cable Network Services, LLC seeks a Data Scientist to utilize background in data analysis, data visualization and machine learning/artificial intelligence to build and implement solutions and utilize the best practices to keep FOX ahead of game.
$159,650 - $175,615 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Under direct supervision from Biostatistician and PI may perform basic analyses on a variety of data formats. Manage Duke internal and multi-site databases, including data cleaning, transformation, importing, and restructuring to uphold data accuracy, integrity, and compliance with institutional policies, with support from the technical team lead and the Program Manager: 15% Training and Documentation (30.
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Data Science tools like Knime, Dataiku, AWS SageMaker, statistical languages, and packages, e.g., R, Python, Julia, SAS, data visualization tools and techniques, e.g., Tableau, ggplot, matplotlib, R/Shiny, Qlik, data manipulation tools such as SQL, Spark, PySpark and Hive, cloud environments like Azure and AWS, deep learning tools such as Tensorflow, Keras and PyTorch.
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data job Title: data specialist Company: Kelly
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