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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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Data Scientist (Senior) NGA - Washington. Experience with Apache Hadoop, HUE, Hive, Pig, Spark, Elasticsearch, Kibana, or Tableau. Bachelors or Masters degree in a field relevant to data science, data analytics, and/or data visualization.
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A minimum of 6 years of experience in designing and implementing complex AI and ML solutions, as a Senior Data scientist, Machine Learning Engineer, or AI Engineer. Knowledge and experience working with Spark or Databricks is a plus.
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Experience with big data platforms such as Hadoop, Spark, and Hive. Collaborate with cross-functional teams including data science, software engineering, and product management to build predictive models, forecasting tools, and recommendation systems.
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Sr Data Scientist @ Atlanta, GA. Typically, Minimum 4 Years Relevant Exp Demonstrated experience with sophisticated analytics tools and programming languages (e.g., SAS, SPSS, R, Python, SQL, HiveQL, Spark, Hadoop) Proficiency with visualization platforms such as Tableau, Qlikview, PowerBI, D3, or JavaScript.
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Mentor junior data scientist in the team with tech lead responsibilities. We are looking for a Senior Data Scientist to join the Inventory & Marketplace quality team. Experience running heavy workloads on a distributed computing cluster (especially EMR or Databricks), leveraging technologies like Spark to work with large datasets.
$123,900 - $227,200 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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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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With over 900 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact.
$156,000 - $255,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Senior Manager, Data Scientist, you will be responsible for both driving the development and implementation of data science strategies, as well as managing a teams of data scientists.
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Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers.
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They work on a team made up of analyst(s), developer(s), data scientist(s), and a product lead, and everyone on the team collaborates in support of a specific mission. The Data Engineer performs validation and analytics corresponding with client requirements and evolves solutions through automation, optimizing performance with minimal human involvement.
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Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. We are seeking a Senior Applied Scientist to build out adaptive and deeply personalized shopping experiences tailored to the customer's shopping journey.
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The Data Scientist is a key role in the transformation of business. Senior Data Scientist. Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc.
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Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) Synaptics is seeking a Sr. Staff Data Scientist to establish the data science function in Synaptics with initial focus on New Product Introduction and Enterprise Sales.
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Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets.
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