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Integrating Databricks with other AWS products such as SNS, SQS, and MSK.What we are looking for: Bachelor's or master's degree in computer science, Information Technology, or a related field.
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Alternatively, must have a Masters degree in Computer Science, Information Systems, Business, Accounting, Finance, Data Science, Engineering, or a related field and 4 years of work experience in one or a combination of the following: IT Audit and/or Financial Services.
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Enrolled in a STEM undergraduate or graduate program (mechanical engineering, aerospace engineering, materials science, electrical engineering, etc.) To enable test execution and analysis of performance data, this role may include aspects of mechanical, electrical, instrumentation, and software engineering.
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Qualifications Bachelor’s degree in computer science, Data Science, or data engineering 3-5 years of experience as a Data Analyst with exposure to data governance practices.
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Candidates will be considered from any specialization within surface processes/geomorphology; those focusing on coastal processes, natural hazards, or the cryosphere, and who use tools such as numerical modeling, remote sensing, and big data science are especially encouraged to apply.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Our team of experts delivers unrivaled insights and leading data and technology solutions, partnering with customers to expand their perspective, operate with confidence, and make decisions with conviction.
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The Trauma Registrar is responsible for the collection/abstraction of required state and national trauma data bank elements into the Trauma Registry database on all patients meeting state or national trauma inclusion criteria.
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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. 7+ years of data engineering experience, at peer firms utilizing agile methods and modern SDLC processes to deliver quality technological solutions in a transparent, reliable way.
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New York Institute of Technology's six schools and colleges offer undergraduate, graduate, and professional degree programs in in-demand disciplines including computer science, data science, and cybersecurity; biology, health professions, and medicine; architecture and design; engineering; IT and digital technologies; management; and energy and sustainability.
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We work closely with other Treasury-Finance teams (Liquidity Management and Capital Markets), Stripe's Information team (Data Science and Data Engineering), Stripe's Money Movement & Storage (MMS) product and engineering teams to build great capital and financial risk infrastructure.
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Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting, advanced RAG and fine-tuning. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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Our team collaborates multi-functionally across the DTC organization and partners with different business functions such as Data Science, Business Operations, Product, Marketing, Engineering, Finance, and more to generate insightful, compelling, and strategic analyses and recommendations.
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Experience in data collection from systems like ServiceNow, Splunk, or other data lakes, along with the ability to extract and normalize data for the establishment of routine feeds for IAM processes.
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Bachelor s degree (or foreign education equivalent) in Analytics, Data Science, Advanced Computer Science, Computer Science, Engineering, Information Technology, Information Systems, Mathematics, or a closely related field and five (5) years of experience as a Senior Manager, Data Science (or related occupation) researching and building scalable AI solutions using ML and Natural Language Processing (NLP) models and technologies to improve customer experience and drive business results.
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10+ years of professional experience in data infrastructure (including data warehousing, ETL processes, and scalable data architectures), data engineering, and/or data science roles, with a focus on HR data.
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