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You will work as part of a cross-functional agile team that includes data scientists, machine learning engineers, software engineers, designers, and product managers. 1+ years of hands-on experience in one of the following technical domains: machine learning, recommendation systems, pattern recognition, NLP, artificial intelligence, or a related technical field.
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Machine Learning Engineer, NeRF. The ideal candidate will have a strong background in computer vision, machine learning, and deep learning, as well as experience working with neural radiance fields.
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Partner with colleagues in data science and machine learning (DSML) and in corporate development to identify critical data assets and/or commission the generation of data for biomarker discovery in neuroscience.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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As the “front door” of personalization and discovery, Search helps millions of listeners fall in love with the depth of our content catalog across Pandora and SiriusXM. In this role, you will leverage your expertise in machine learning, information retrieval, ranking, natural language processing, and recommendations to frame business goals as machine learning problems, research novel methods, and build machine learning systems for Search and Voice.
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As a Machine Learning Engineer on the Banking & SFS team, you will support fellow Data Scientists and Modelers in building and deploying machine learning models that support our banking and lending business.
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An advanced degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline. Equilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software & ML engineering.
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Perform data exploration using a combination of statistical programming languages (including, but not limited R, Python, SQL, SAS) and deploy predictive analytics and machine learning techniques to improve risk prediction, improve reserve, trend and financial forecasting in a manner that is actuarially sound, and enable real-time results and operational efficiencies.
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Including two-thirds of high school students and half of all college students in the US. Combining cognitive science and machine learning, Quizlet guides students through adaptive study activities to confidently reach their learning goals.
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This role will coordinate with our hardware team to improve data collection from our novel spectral soil probe for building machine learning models, will partner with our soil science team to collect and analyze soil and geospatial data sets, and will collaborate with our business development team to accurately and effectively communicate soil carbon results to our customers.
$140,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Familiarity with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch) for analyzing Earth observation data in the context of carbon monitoring and climate analysis is advantageous.
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The incumbent will apply advanced data analysis skills and machine learning in collaboration with a group of computational and biological scientists to perform translational oncology research around multimodal translational data sets for programs in clinical development.
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Advanced proficiency with data, analytics, and visualization technologies (we use SQL, Looker, and Python). As a Data Scientist on the Square Loans team, you will partner with cross functional stakeholders like Product, Credit Policy, Engineering, and Operations to shape and execute strategies that expand credit eligibility, enhance loan gross profit, and improve cohesive banking user experience on a global scale.
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The Director, AIML Security will work within GSK’s Cyber Risk Operations team, interacting directly with stakeholders and technical teams to drive and support the key programs and projects related to Artificial Intelligence (AI) and Machine Learning (ML.
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Foundational Knowledge of Google Big Query, Node.js, CSS, Python, Domo, machine learning concepts. Experience with Google Big Query and creating data ingestion pipelines from multiple online and offline sources.
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