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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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The Asset Management Quant Research Engineering team is looking for a Principal Quant Data Engineer who wishes to take on the challenge of building a world-class data operation. Deliver datasets from onboarding through mapping and automated DQ so they can be handed off to the Data Operations team for DQ maintenance and consumed by research teams and production.
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At J.Jill, our success is guided by a culture that values the intrinsic art of creativity and the data science required to drive our future growth. We are collaborative and data-centric, with every associate focused on creating our customers unique experience and delivering results through our omnichannel business model.
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Lead data engineer role with a major Financial Services company. Metadata capture and catalog services for data lake (S3/ Athena), data warehouses (RDS/ Redshift), Microservices/ APIs.
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SSIS strongly preferredPython DBT, Mulesoft, Alation – good to havePrimary Responsibilities:Strong understanding or Snowflake on Azure Architecture, design, implementation and operationalization of large-scale data and analytics solutions on Snowflake Cloud Data Warehouse.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. For data Science/Machine learning Positions. Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT.
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Act as a conduit between MongoDB Data Science and business stakeholders across GTM pillars, including but not limited to Sales, Marketing, Growth and Customer Success organizations. We are growing adoption of data science models across the business, and you will help us increase this velocity substantially.
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Designs, develops, and implements ETL/ELT processes using Azure Data Factory, Synapse pipelines, Databricks Notebooks, Event Hub to build integrations from Saas sources such as Service Now, Workday, Dynamics CRM, and Eloqua.
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Solidly established Global FinTech Firm is looking for an analytics savvy, data driven individual to join its Human Resources Analytics and Products Team as a People Analytics-Data Science & Reporting Analyst.
$115,000 - $175,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Sr. Technology Risk Data Engineer - Financial Services (Python/SQL) Experience - Minimum 5 years of experience with proven working experience as a data engineer or data analyst.
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The Department is home to research labs in AI, machine learning, computer vision, big data analytics, programming languages, cryptography, computer security, and software systems, and is the main constituent of the Stevens Institute for Artificial Intelligence (SIAI), an interdisciplinary research center that brings together over 100 faculty members across the University.
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Excellent written and verbal communication and presentation skills, ability to communicate quantitative concepts to financial professionals Knowledge of prepayment modeling, MBS pricing and risks is a plus Knowledge and experience on data science and Machine Learning technics/languages is desired SEC Covered Clearing Agency Standards Additional Qualifications.
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Knowledge of real-time data streaming and real-time analytics Knowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory) Strong implementation skills and working knowledge of data structures, algorithms and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using Spark.
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At Fit:Match, you would work cross-functionally with another top global talent with experience in the technology, data science, apparel design and fit, marketing, and retail industries. Cloud Services: AWS Console, Amazon EC2, Amazon S3, AWS Lambda, Amazon RDS, DynamoDB About the Company Fit:match is a B2B2C technology company on a mission to revolutionize the apparel industry through data science to deliver increased relevance and satisfaction for shoppers, improve retail economics and help the industry as a whole make significant strides towards sustainable apparel retail.
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DAAR team is seeking a Data and Research Assistant to support our pretrial Supervised Release work in New York City. Since its launch in 2016, the NYC Supervised Release Program (SRP) has diverted over 40,000 people from monetary bail and likely pretrial detention, and following legislative amendments to New York’s bail statute, the program continues to evolve.
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data science jobs Title: engineer Company: Capital One in New York, NY
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