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Technical Acumen:Perform model training and validation using various types of machine learning techniques on structured/unstructured data, including imagery, text and graphs. Technical Oversight:Provide technical guidance on model training and validation using various machine learning techniques on structured/unstructured data, including imagery, text, and graphs.
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Leverage Azure Databricks for big data processing, machine learning, and analytics workloads. Knowledge of advanced analytics, machine learning, and AI integration is advantageous.
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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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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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For data Science/Machine learning Positions. Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools. Preferred skills: NLP, Text mining, Tableau, PowerBI, Databricks, Tensorflow.
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Work closely with the data scientist and innovation lead on A.I. and machine learning initiatives. Strong proficiency in analytical tools and software, including SQL, Python, R, and data visualization tools such as DOMO, Tableau or Power BI.
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Understanding of AI/ML machine learning and predictive modeling techniques. Demonstrated experience with enterprise data, especially ERP systems (SAP, JD Edwards, SFDC etc) & Integration patterns.
$180,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Experience using Statistical and Machine Learning algorithms on real data, in commercial environments. Familiarity and experience with the standard machine learning packages, such as numpy, scipy scikit-learn, TensorFlow, keras and Theano.
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Expert in data analysis, machine learning, statistical modeling, and data manipulation. Proficient in tools and languages like Python, R, SQL, and machine learning libraries/frameworks.
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Working under general direction of the Principal Investigator, this position provides analysis and develops and evaluates natural language processing and machine learning algorithms to leverage electronic health record data to support clinical care and research in the neuroscience.
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Job Responsibilities: Team Leadership and Development: Lead, mentor, and develop a team of data scientists and machine learning engineers. Job Description: Lead a highly motivated hybrid-remote team tackling diverse AI projects ranging from traditional machine learning to cutting-edge imagery and LLM. Take ownership over your work, embrace continuous learning, and above all, find joy in what you do.
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The ideal candidate will have strong skills in SQL, Python, and machine learning algorithms, along with a proven track record of solving complex data problems. Strong programming skills in Python for data analysis and machine learning.
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You understand the data science lifecycle and are experienced in development and implementation of advanced statistical models and machine learning algorithms. We focus on an “AI First” mindset and are helping clients tackle unique and challenging problems with a full suite of AI tools (Generative AI, “traditional” AI, machine learning, and data science.
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This position will be based in our corporate headquarter in Fairfield, Ohio. This intern will work in the innovation analytics team with a focus on machine learning and modeling preparation.
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Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools. Understanding of metadata management, data lineage, and data glossaries is a plus.
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machine learning jobs Title: data in Dallas, TX
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