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Educational background in African American History, Social Sciences and/or Political Science, Library Science, or Archival Management. Advises the Department in the creation, development, and implementation of collections management policies; archives procedures; procedures manual; departmental goals, and preservation planning.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Certified Analytics Professional (CAP), Data Science Council of America (DASCA), Principal Data Scientist (PDS), SAS Big Data Professional, Microsoft Certified Azure Data Scientist Associate, or equivalents.
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As our first Data Science hire focusing on Machine Learning at Circle, you'll start by focusing on two critical problems: helping identify transactions and actors who might be acting illicitly and helping us better balance our reserves across a series of accounts to reduce systemic risk inside the company.
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Master’s degree in Business Analytics, Statistics, Computer Science, Applied Mathematics, Data Science, MIS, Management, Operations Research, Industrial Engineering, or a related field.
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Bachelor's degree or graduate education in meteorology, atmospheric or environmental science, environmental management, urban planning, GIS, environmental engineering, or related field. Serve as a climate science subject matter expert, performing meteorological and climate data analysis, including regional climate profiling guiding teams on the use of climate data and tools for assessing natural hazard risk.
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While the focus of this job will be machine learning applications, there are times where we need to use data science to solve other problems, and machine learning is not the only or optimal option.
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Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g., regression, classification, Time Series analysis: e.g., ARIMA, Traditional machine learning methods: e.g., Random Forest, ensemble model techniques, Optimization: e.g. linear programming.
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The Data Science Team within Customer Success is highly engaged with our clients making use of their critical thinking skills with a business-focused mentality and customer-facing attitude.
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Economics, Statistics, Applied Mathematics, Mathematics, Financial Mathematics, Data Processing/Analytics/Science. As a Senior Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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The Data Science Internship provides c graduate students with an opportunity to sharpen their leadership, technical, and business skills through a 10-week working and learning experience.
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Founded in 2003, iParametrics is a recognized leader in emergency management, homeland security, cost estimating and data analytics for federal, state, and local clients, including the Department of Homeland Security (DHS), the Federal Emergency Management Agency (FEMA), the Department of Energy (DOE), the Department of Defense (DOD.
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We're seeking a Sr. Data Scientist to join our dynamic team and play a pivotal role in developing advanced data science and analytics order management capabilities. Shape the Future of Order Management at Home Depot with Data Science & Analytics.
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Experience in data science, machine learning, or NLP, with a significant focus on both unstructured and structured data analytics with 3+ years of hands-on experience developing and deploying traditional NLP solutions (non-LLM & non-GenAI) in an enterprise setting, covering topics like text classification, named entity recognition, sentiment analysis, and more, additionally, 2 years of experience in building impactful LLM-based applications and POCs is required.
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data science scientist management jobs in Atlanta, KY, United Kingdom
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