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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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Undergraduate teaching experience in core topics in Data Science such as programming, data mining, data visualization, Parallel and Distributed Computing, Machine Learning, Big Data Engineering and, Probability and Statistics will be considered an asset.
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In Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.
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As a Data Science Sr. Manager at CarMax, you’ll apply your passion and expertise in data, machine learning, and entrepreneurship to create data-science applications that enrich CarMax’s culture of innovation.
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Previous experience in a technical role such as a data scientist, solutions architect, machine learning engineer, AI consultant, etc. SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI.
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3 years of experience in executing and deploying data science, machine learning, deep learning, and Generative AI solutions in a large-scale enterprise setting (fewer years may be accepted with a Masters or Doctorate degree.
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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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As a Lead Data Scientist on the Network Configuration team, you will play a crucial role in developing cutting-edge machine learning solutions. Craft compelling narratives and visually appealing content to engage and inform senior executives on strategic initiatives, progress, achievements, and key metrics of data science and analytics projects.
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As a Data Scientist at Capital One, youll be part of a team thats leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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In Machine Learning, Computer Science, Electrical Engineering, Statistics, Applied Math Benefits & Perks Equity Package 15% Bonus Generous Paid-Time Off 401k Match 100% Coverage for Medical, Dental, and Vision Relocation Package Included Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
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As a Senior Data Scientist, you will partner with Machine Learning Engineers, Data Engineers, Data Analysts and other professionals to build state-of-the-art prediction, optimization, engagement, and behavioral models.
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The Analytics Experience team, which is part of the Artificial Intelligence, Data and Advanced Analytics (AIDA) organization is responsible for the creating a seamless experience for analytics experts to harness the potential of big data, machine learning, and interactive analytics through a unified platform across the enterprise – from scientific/clinical to commercial across all Pfizer geographies.
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Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
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Emerging ML is the data science and machine learning team inside Capital One’s Applied Research organization. Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms.
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You’ll conduct quantitative research to inform product strategy and opportunities, design metrics to help track goals and make decisions, devise learning methods (including experiments) to test hypotheses, and work closely with our machine learning and data engineering teams on building MVP user-facing data products.
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data science machine learning on jobs Title: data in Manhattan, NY
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