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An HR Data Analyst may work on various projects related to talent acquisition, performance management, employee engagement, diversity and inclusion, compensation and benefits, learning and development, and more.
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The Department of Computer Science has 25 teaching-track faculty and 56 tenured and tenure-track faculty with wide-ranging research interests, and strong research groups in cybersecurity, systems and networks, machine learning and data mining, artificial intelligence, robotics, visual computing, theory, databases, bioinformatics, HCI, and software engineering.
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Our high-performing team works with clients to implement the full spectrum of data analytics and data science, ranging from data architecture design, data engineering and querying, data visualization and dashboarding, predictive analytics, machine learning, and artificial intelligence.
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Architect/Developer should have strong technical experience in data analysis, business intelligence, and/or data science. Should possess ability to work with a variety of software to include but not limited to SQL Server Integration Services, Azure Data Factory, Microsoft SQL Server Reporting Services, Data studio, Databricks and can work with a variety of languages and data formats such as parquet and json.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Process data and information at massive scale as an Artificial Intelligence (AI) and Machine Learning (ML) Engineer with machine learning technologies. Experience with creating benchmark datasets and Python packages to facilitate data science objectives.
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You will function as part of a world class Data Science team to support various AI and machine learning initiatives Solve complex marketing and business challenges by accessing, integrating, manipulating, mining, and modeling a variety of data sources Reframe client business questions into data science deliverables.
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We are seeking an engineer with a technical background in one of the following disciplines: systems engineering, applied operations research, modeling and simulation, RF and satellite communications, artificial intelligence and machine learning (AI/ML), or applied data analytics.
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Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, or computer programming to large data sets. Freddie Mac’s Modeling, Econometrics, Data Science & Analytics Department is currently seeking a Quantitative Analytics Senior who will be responsible for the development and execution of quantitative analytics and modeling projects in support of Freddie Mac’ business.
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Job Description General Summary The Healthcare Data Scientist - Machine Learning/AI, Statistics, Operations Research position will join our Advanced Data Science group at the University of Maryland Medical System (UMMS) in support of its strategic priority to become a data-driven and outcomes-oriented organization.
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PhD in Computer Science, Engineering, Applied Mathematics/Statistics/Data Science, or any quantitative field. 10+ years of relevant industry experience as a data and machine learning engineer, with a strong track record of shipping successful AI/ML products at scale.
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Four (4) years relevant experience in applied research, big data analytics, statistics, applied mathematics, data science, computer science, operations research or other closely related other quantitative or mathematical discipline.
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The Machine Learning/Data Science Research Engineer will participate in an end-to-end design and implementation of deep learning solutions for application in network/graph representation learning (NRL) and graph construction/generation/completion.
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As a Principal Data Scientist, you will lead innovative data science projects and teams, using your expertise in machine learning, particularly Time Series, Natural Language Processing (NLP) and Large Language Models (LLMs), to develop scalable, ethical solutions that transform customer interactions with their finances.
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Responsible for overseeing a team of data analysts and data scientists to provide analytical support through machine learning, statistical analysis, causal analysis, and modeling and simulation within the people analytics team.
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