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The OR/SE also elicits information from Subject Matter Experts (SMEs) and stakeholders, and iterates with them to develop qualitative models of their expertise and/or needs and utilizes applied statistical analysis, machine learning, optimization, and visualization to support defensible decisions and decision processes.
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Deep understanding of data modeling, ETL processes, and machine learning concepts. We are looking for a highly motivated and skilled Product Manager to lead the conceptualization, development, and optimization of our data pipelines and machine learning projects.
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Recognized industry expertise in 2-3 of the following: Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning and Statistical modeling. Travelers Data Scientists are taking the organization to the next level of intelligence by using advanced statistical techniques and machine learning algorithms.
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Experience in developing AI/ML based products with exposure to advanced analytics, predictive modeling and machine learning features. We are seeking an experienced Principal Product Manager to join our Payables team within Oracle Cloud ERP to embark on the journey with us in defining the next generation of finance functions, mainly around Procure to Pay Process.
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Minimum of 3 years of experience in a data science role, with a strong foundation in statistical analysis, predictive modeling, and machine learning. Develop and implement statistical models and machine learning algorithms to analyze large datasets and extract actionable insights relevant to public health initiatives.
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Experience with data science tools and programming languages such as Python, R, SQL, and big data technologies. DHP develops and maintains a variety of data and information systems to support its mission, including systems to collect, transmit, store, and analyze data for HIV/AIDS surveillance, epidemiology, and program monitoring and evaluation.
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Expert command of AI and machine learning, statistical modeling, state-of-the-art tools, and engineering best practices. In this role you will be building and deploying machine learning models using both analytical algorithms and deep learning approaches.
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Develops new approaches to leverage best-in-class technology (e.g., Machine Learning, Artificial Intelligence, Predictive Analytics etc.) Key Focus Areas: Optimize P&L to fuel growth; Drive P&L standardization and simplification; Partner with SE&O (Sales Enablement & Operations) and organizational units conditions of satisfaction in landing & governance of blueprint; Set Investment Principles/ Lead investment decision governance; Enhance End-Customer Investment Funding (ECIF) Effectiveness; Resource and Productivity Modeling; Hierarchy Management.
$91,800 - $195,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Experience with stochastic computational modeling, data science, and machine learning applied to disease forecasting. jl, Numpy, JAX, Numpyro, and Stan for Bayesian inference, computational modeling efficiency, parameter estimation, and model validation.
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2+ years of experience in machine learning with domain knowledge and experience in the following areas: data-driven statistical modeling, discrimination methods, feature extraction and analysis, supervised learning.
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The LCRR Regional Lead will work closely with the Specialized Solutions group to apply dashboarding capabilities, advanced data analytics, and machine learning for predictive modeling of SL material identification but will not be responsible for development of these tools.
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Machine learning or deep learning algorithms, natural language processing techniques. Apply statistical, machine learning, and NLP techniques to identify patterns, extract meaningful insights, or develop new tools or solution for the business stakeholders.
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Shape development of new insights based on Data Science methods such as Machine Learning, probabilistic modeling, Natural Language Processing, Price Elasticity modeling, Price Sensitivity modeling, etc.
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Hands-on experience with machine learning libraries/frameworks such as scikit-learn, TensorFlow, or PyTorch. As a Supply Chain Data Science Consultant, you will leverage your expertise in data science, machine learning, and supply chain management to help clients optimize their supply chain operations.
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Advanced knowledge of machine learning modeling techniques (clustering, decision tree learning, and NLP) and their real-world advantages/drawbacks. In this role, the successful candidate must have a demonstrated understanding of machine learning concepts, data engineering techniques, and presentation-ready reporting.
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modeling machine learning jobs in Atlanta, GA
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