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Successful candidates for this role must have very strong analytical and research skills, a deep understanding of statistics and statistical modeling, a strong understanding of modern machine learning and its mathematical underpinnings, and they must have very strong programming skills with SQL, and R, Python.
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Statistical Background: Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data. Within LSEG, the Power, Natural Gas, Coal, and Carbon Research division (formerly known as Point Carbon, Thomson Reuters, and Refinitiv) has a strong presence in the commodity community.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Demonstrating a thorough level of knowledge in statistical modeling, algorithms, data mining, and machine learning algorithms problem solving.
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Experience of predictive modeling with machine learning. Equipment Utilized Should have statistical programming skills and experience (Stata, SPSS, SAS, R, or JMP, etc. Certifications/Licenses Required Knowledge, Skills, and Abilities Statistical programming skills (Stata, SPSS, SAS, JMP, or R, etc.
$88,210 - $135,093Full-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Familiarity with advanced statistical and machine learning techniques such as clustering, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms is a plus.
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Proven track record of Problem Solving, Data Analysis Skills including statistical analysis and modeling or computer programming (SQLPathFinder or JUMP Script or Python or AI/Machine Learning.
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Demonstrating intimate knowledge about designing and implementing data-driven analyses to monitor for compliance with regulations and standards, such as anti-corruption laws, data privacy regulations, and industry-specific regulations.
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Utilizing statistical analysis, unsupervised machine learning, supervised machine learning, and deep learning, as needed. Have 5+ years of experience (2+ years of experience if Masters or Doctoral degree) in the machine learning and data science fields; OR completed and have a strong interest in linear algebra, calculus, statistics, probability, or related coursework.
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A deep understanding of statistical and predictive modeling concepts, including machine-learning or data mining approaches. Master’s degree with a very strong academic background in statistics (e.g. mathematics, statistics, computer science, data mining, machine learning, operations research, physics or a related quantitative discipline.
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Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). 10 years of experience in AI applications (e.g., Deep Learning, NLP, Computer Vision, or Pattern Recognition.
$215,000 - $315,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Responsibilities:Total 7+ years of hands-on experience with advanced machine learning, data mining, statistical inference, mathematical modeling and deep learning techniques.
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Specialized experience for this position must include: Experience with data science and analytical methods from conducting machine learning, Natural Language Processing, and technical procedures such as, solution design, implementation, and deployment.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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The Data Scientist is responsible for analyzing and interpreting large and complex data sets, developing predictive/ machine learning models, NLP techniques and communicating insights to various stakeholders.
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As an AI Machine Learning Engineer focus will be on designing and developing scalable solutions using AI tools and machine learning models. Knowledge of a variety of machine learning techniques (semantic segmentation, clustering, decision tree learning, artificial neural networks, etc.
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machine learning statistical jobs
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