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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch.
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Program cognitive tasks, software pipelines, data visualization tools, and machine learning or data science utilities for a variety of scientific use cases. The Scientific Software Engineering Generalist responsibilities include writing, debugging, and testing code for arbitrary signal processing and data analysis tasks, software packaging, and the development of training resources.
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Full stack software engineering experience, with proven experience in data visualization modules or frameworks like Python Dash and R Shiny. 3+ years of hands-on experience as a quantitative developer developing financial models and software solutions.
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BA/BS degree in Data Science, Statistics, Computer Science, Engineering, Public Health Information, Bioinformatics, or equivalent quantitative field. Demonstrated data mining technical knowledge and skills for use in decision trees, multivariate analysis, segmentation modeling, factor analysis, regression analysis, forecasting, machine learning, etc.
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8+ years of experience in data engineering or full-stack quantitative analytics/data science roles. Stay current with emerging trends and technologies in the data engineering field, incorporating them into the organization's data strategy.
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Serves as an informal mentor by leading by example to support and assist students as encouragement for college readiness, particularly in science, technology, engineering, and mathematics (STEM.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Silver HCM Excellence Award for Learning & Development” – Brandon Hall Group. Prior experience with Radiology Information Systems, PACS, Data processing and digital data transfer process.
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10+ years of experience in design, planning, and implementation of stormwater and hydraulic elements with a focus on project management Proven track record of successfully managing water resource engineering projects, including drainage systems, flood control, and watershed management.
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Collaborate with different teams in EDM (Data Cloud, Architecture, Data Governance Tech, Data Science) and support strategic initiatives such as data governance, data-as-a-service, and self-service analytics.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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A software engineering industry certification, including but not limited to: Certified Scrum Developer (CSD), Certified Scrum Master (CSM), Certified Software Development Professional (CSDP), Certified Secure Software Lifecycle Professional (CSSLP), Amazon Certified: AWS Certified Developer, Microsoft Certified: Azure Developer, Certified Software Test Professional (CSTP.
$156,275 - $184,456 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The ideal candidate will have a strong background in software development, natural language processing (NLP), and machine learning (ML), along with a passion for creating intuitive and user-friendly conversational interfaces.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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As a product manager on our Trust & Safety team, you will work with data science, policy, algo, engineering, operations, and various relevant internal teams across the globe to form strategies and build features that ensure users are safe on our platform.
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data science software engineering deep learning jobs Title: engineer in Kearny, NJ
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