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Data Engineers on the Disney Streaming Machine Learning and Innovation team develop and maintain systems and datasets that are used for Fraud/ATO/Bot Detection on Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. In this role you will partner with Applied Machine Learning Engineers and Data Scientists to help manage and scale processes to create algorithm input features and datasets.
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The leadership for the NSF-Simons Center - The Southeast Center for Mathematics and Biology - is in the School of Math at Georgia Tech. Furthermore, the School is a key partner in several programs at Georgia Tech, including PhD programs in Bioinformatics, Quantitative Biosciences, Biostatistics, as well as Algorithms, Computation and Optimization, Computational Science and Engineering, and Machine Learning.
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This candidate should be proficient in using BI tools such as Tableau, in addition to experience with one or more modern technologies such as relational databases, AWS, Snowflake, Python, Databricks, Git, and Machine Learning.
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Hands-on experience with data analytics and classical machine learning tools(like pandas, NumPy, scikit-learn)and deep learning frameworks(like Tensorflow, Lang Chain, Pytorch, Flask, Fast API.
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Strong background in machine learning, statistical modeling, and data mining. 3-5 years of experience in applying deep learning methods to text data, including natural language processing, text classification, sentiment analysis, or other related applications.
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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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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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Experience in Natural Language Processing, Machine Learning Ops and data pipelines. Lead Machine Learning Engineer. Serve as a subject matter expert in machine learning and fintech domains.
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure) Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
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Our transformative solutions are powered by artificial intelligence, machine learning, facial recognition, cloud solutions and Big Data analytics. Our transformative solutions are powered by artificial intelligence, machine learning, learn from new insights, and seize new opportunities.
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Responsibilities: · Responsible for the administration, configuration, and optimization of the Databricks platform to enable data analytics, machine learning, and data engineering activities within the organization.
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Amazon Web Services (AWS) is looking for a world class partner leader to drive enterprise digital transformation initiatives with strategic technology partners in the Artificial Intelligence/Machine Learning Sector.
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Apply familiarity and skill with additional programming languages (e.g., Python, R), statistics, machine learning tools, data structure, data modeling, cloud computing, MS Azure, and Databricks to expand and enhance surveillance data value.
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Understanding of Master data management, data visualization and story building, data science and machine learning is highly preferred. WHAT YOU WILL CONTRIBUTEThe Data and Analytics Director is accountable for the strategic governance and management of the North America Data and Analytics team.
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Integrate advanced analytics and machine learning capabilities into the repository to enable data-driven insights, predictive modeling, or anomaly detection. The candidate shall independently provide system updates and enhancements, organizational processes, and systems to improve the effectiveness of both organizational strategy and operations of programs supported by DHP. This will include updating, enhancing, and maintaining the data repository and internal Power BI-based DHP Dashboard, and other program management tools to track progress efficiently and effectively toward national goals and manage/monitor DHP recipients.
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machine learning data jobs in Atlanta, CA, Arkansas
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