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Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive, predictive analytics and modeling Leverage a broad set of modern technologies – including Python, R, Scala, and Spark – to analyze and gain insights within large data sets Manage, architect, and analyze big data in order to build data driven insights and high impact data models Evaluate model design and performance and perform champion/challenger development.
$112,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Data Scientist at Capital One, youll be part of a team thats leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. San Francisco, California (Hybrid On-site): $213,400 - $243,500 for Manager, Data Science.
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Experience in modern programming languages like JavaScript, Typescript, Node, Java, Python, etc. Experience with a RDBMS (SQL) or a NoSQL data store a plus4. Experience in modern programming languages like JavaScript, Typescript, Node, Java, Python, etc.
$270,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Your key responsibilities You'll spend most of your time working with a wide variety of clients to deliver the latest data science and big data technologies and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources.
$158,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Emerging ML is the data science and machine learning team inside Capital One’s Applied Research organization. At least 2 years’ experience in Python, Scala, or R for large scale data analysis.
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Experience with data engineering and big data technologies such as Apache Airflow, Trino, and AWS EMR. B.S. in Computer Science (or equivalent experience) and at least 3 years professional experience working as part of an Agile team using DevOps practices and modern programming languages and frameworks to develop and engineer data-related services and applications to cloud platforms.
$155,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Data engineering and big data technologies such as Apache Airflow, Trino, and AWS EMR. Modern programming languages and frameworks including Python (FastAPI, Django, Flask), JavaScript (Node.js, Express, Vue, Svelte, React), and Java (Spring Boot.
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San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Mgr, Data Science. New York City, New York (Hybrid On-Site): $201,400 - $229,900 for Manager, Data Science. New York City (Hybrid On-Site): $201,400 - $229,900 for Mgr, Data Science.
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Proficiency in big data modeling work: Hadoop, Pig, Scala, Spark. You will work on vast amounts of Drug Enforcement Agency (DEA) data to discover hidden information by applying modern statistical and ML/AI techniques.
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Deliver insights to help our clients turn data into action as a Data Scientist at GDIT. Your work will provide transformative solutions to our clients' big-data obstacles and help advance the mission.
$135,530 a yearFull-timeExpandApply NowActive JobUpdated 26 days ago - UpvoteDownvoteShare Job
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Job Description Deliver insights to help our clients turn data into action as a Data Scientist at GDIT. Your work will provide transformative solutions to our clients' big-data obstacles and help advance the mission.
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Our cross-industry solutions are powered by modern technology, market intelligence, and big data to drive purposeful change and actionable outcomes. We are looking for a Data Scientist who will support our client teams with insights gained from analyzing data leveraging advance analytics techniques.
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