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ML Ops: Design and Build customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsTechnical Expertise: Serve as the subject matter expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains.
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Audible Content Data Science team partners with business, technology, and product leaders to solve problems related to Content Understanding, Content Evaluation, and Recommendations, relying on Natural Language Processing (NLP), ML, Deep Learning, LLMs/GenAI. We operate in an agile environment in which we own the life cycle of research, design, model development and, often, deployment.
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Mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories, heart rate, breast cancer, maternity.
$149,500 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing machine learning models with business impactExperience with machine learning methods in Recommendation System, Search, Causal Inference, Optimization, Time Series, Natural Language Processing, Large Language Model, Computer Vision.
$140,100 - $210,100 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience & Skills•Demonstrated expertise in AI technologies, including machine learning, natural language processing, and computer vision. Education: advanced degree (Master or PhD) in computer science, engineering, data science, law, policy, ethics, or related field.
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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. Expertise (5+ years experience) in one data modality of MoBI: EEG, physiological measures, eye-tracking, natural language processing, developing computer-based tasks, or ecological assessments is preferred.
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Strong mathematical background with strong knowledge in at least one of the following fields: statistics, data mining, machine learning, statistics, operations research, econometrics, natural language processing.
$55,000 - $136,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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The Team: S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team.
$180,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
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R and R Shinny are a must have for any Data Scientist or Machine Learning Engineer. Master Degree in Computer Science, Applied Mathematics, Physics, Statistics or Applied Statistics field is a must too.
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Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. Ph. D (preferred), Bachelor's or Master's degree in Computer Science, Mathematics or Statistics , Computational linguistics, Engineering, or a related field.
$180,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
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The ideal candidate will have a strong background in AI, machine learning, and data science, with a proven track record of designing and implementing AI systems. Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
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Experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment.
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DE designing and implementing large scale data science projects, Artificial Intelligence (AI) and Machine Learning (ML) models and interfaces using Spark, Tensorflow, Python data science libraries, and Deep Learning (DL) frameworks on Amazon Web Services (AWS) and On-premise computing environments; developing cutting-edge investment tools and strategies using Natural Language Processing (NLP), Large Language Models (LLM), Neural Networks, and Supervised and Unsupervised Learning algorithms.
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machine learning data science natural processing computer jobs in New York, NY
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