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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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Under this program, we will make you stand out from the rest of the jobseekers by offering Skill enhancement training on the technologies in-demand including time management skills, study skills, test-taking skills, and learning strategies after which we can assist candidates in getting jobs as software programmers / Java Programmers / Data scientists / Machine learning engineers / Data analysts.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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Minimum Qualifications: Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a related fieldAt least 3 years of experience as a Data Scientist, with a focus on developing and deploying machine learning models in production environmentsStrong programming skills in at least one language (Python, SQL, Spark, C.
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Design and implement end- to- end solutions using Machine Learning, Optimization, and other advanced computer science technologies, and own live deployments to drive advertising conversion.
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As a Quantum Computing Research Scientist Vice President within the Global Technology Applied Research (GTAR) center at JPMorgan Chase & Co., you will have the opportunity to advance the theoretical understanding of quantum algorithms for optimization, stochastic modelling, numerical analysis, machine learning and financial use cases.
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Hands on experience in dealing with structured and unstructured data from multiple sources and applying machine learning techniques and algorithms to discover patterns, intents and build knowledge repositories and graphs to solve enterprise problems.
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The Risk Management & Compliance Technology Machine Learning team at JPMorgan Chase focuses on solving challenging business problems such as Anti-Money Laundering and Surveillance through data science and machine learning techniques across Risk, Compliance, Conduct and Operational Risk. Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area.
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In addition, the group extracts relationships insights by applying - distributed - graph, machine learning, and natural language processing algorithms on this Knowledge Graph, as well as on other text document collections, and feeds these insights, via means of reliable and scalable APIs, UI applications, and mobile applications, to several other firm products and employees across multiple divisions: Compliance, Investment Banking, Global Markets, Asset Management, to name a few.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. Director, Model Validation for SHUSA Compliance models (Transaction Monitoring, Sanctions Screening, Fraud Risk, etc) will be responsible for leading the independent validation of models used by various Compliance groups in conformance with regulatory guidance on model risk SR- and other regulatory requirements around Compliance models.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. On any given day, you might:Evaluate open-source and internally-developed modeling and analytics tools using real business dataIntegrate internal data with external data sources and APIs to discover and implement actionable insightsDesign and craft data science models to communicate solutions to customers and company leadershipWe'd love to find someone who is.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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Participate in the development of appropriate instructional support tools to continuously update internal resources on emerging technologies that are relevant to the NYC Health + Hospitals' learning initiatives and offerings.
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Candidates should demonstrate expert knowledge in one or more of the following areas: data management, machine learning, deep learning, artificial intelligence, data visualization, programming Python, programming in R, databases, and related topics, either through a record of teaching excellence or through industrial experience.
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on machine learning jobs Title: solutions architect in Hoboken, NJ
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