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Knowledge of statistical sampling, optimization, machine learning, predictive modeling, and artificial intelligence techniques. The Client Quantitative Analyst position is within the Client Protection organization supporting functions, including Fraud Prevention and Detection, Anti-Money Laundering (AML), Sanctions and Screening Compliance.
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Help us change the future of work for doctors in the United States by applying state of the art technology solutions, including data API development, modern integration patterns, frameworks for building beautiful, responsive applications, machine learning, natural language processing, and explicable AI - in partnership with key partners.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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Experience with data visualization tools (e.g., Spotfire) and advanced analytics techniques (e.g., machine learning) is required. You will also work with scientists and with experts in data management, lab automation, molecular design, and machine learning in the Global Biologics organization to build and continuously improve data infrastructure.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other AI technologies and platforms; Building machine learning models and systems, interpreting output, and communicating results to internal/client teams and how those outcomes realize business value.
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This position is key for achieving the mission of the Computational Antigen Design: pioneering, testing and implementing innovative cutting-edge biological science and novel Structural Biology/Machine Learning technology solutions and concepts towards antigen design.
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Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology. Ph. D. degree in Computer Science, Machine Learning or a related field.
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Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark. Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (, AWS, Google Data Analytics, Microsoft Azure) Information for applicants with a need for accommodation: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
$198,375 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with a wide range of AI techniques, including machine learning, deep learning, natural language processing, and computer vision. Advanced degree (PhD or MS) in Computer Science, AI, Machine Learning, or a related field.
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In-depth understanding of statistics, econometrics, multivariate regressions, machine learning and other quantitative finance topics. The quantitative analyst is expected to utilize advanced quantitative skills to develop interest rate risk, credit risk and liquidity risk models by directly linking macroeconomic factors to key credit risk drivers for various asset classes held in the investment portfolio.
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San Francisco and San Jose, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer.
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Significant relevant experience after your MD/PhD/postdoc including quantitative expertise in biostatistics, bioinformatics, computer biology, statistical genetics, clinical imaging, machine learning, or data science; interpreting and publishing studies consisting of “omics” data e.g. genetics, genomics, proteomics; closely partnering with/leading data scientists.
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Responsibilities Learning Management SystemServes as NPCS department administrator for the HealthStream Learning Management System, accountable for user experience and answering tickets submitted by users requiring help with the platform.
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San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Lead Machine Learning Engineer. New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Machine Learning Engineer.
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PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree. 4+ years experience in building machine learning and deep learning models for large scale customer facing product of features.
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machine learning jobs Title: devops engineer Company: Amazon Corporate Llc in Boston, MA
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