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Product Data Science (PDS) is the data science team working with the R&D on our core Demand Side Platform (DSP) product, and this role will be within the Infra & Machine Learning (ML) Data Science (DS) team.
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Is experienced with Machine Learning and Deep Learning models and frameworks. If you are looking for an exciting new opportunity as a data scientist to help solve difficult.
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We are looking for a senior data scientist with experience building production ready machine learning models for enterprise scale to help lead transformative change within a F200 company.
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Oracle Senior Principal Speech Scientist Jackson , Mississippi Apply Now Invent, implement and deploy state-of-the-art machine learning models, algorithms and systems as part of the OCI Speech team.
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Strong software engineering skills to create scalable and robust infrastructure for deep learning data, modeling, and evaluation systems. Experience in applying deep learning to robotics problems and predicting multimodal behaviors for agents viatechniques such as MDP, Monte-Carlo methods, TD learning, policy approximations etc.
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Nice to have knowledge in machine learning, deep learning, and natural language processing techniques, with a focus on Generative AI applications. Proven track record of using predictive analytics, forecasting, modeling and data science methodologies in delivering high-impact projects on schedule and within budget.
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We are seeking an Applied Scientist who has a solid background in applied Machine Learning and Data Science, deep passion for building data-driven products, ability to formulate data insights and scientific vision, and has a proven track record of executing complex projects and delivering business impact.
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CompTIA Data+, Power BI Data Analyst, SAS Certified Data Scientist, Certified Analytics Professional, or other relevant professional designation or advanced degree. Advanced knowledge of information security and systems, application controls and emerging technology utilization including but not limited to artificial intelligence, machine learning, deep learning, advanced process automation, cloud and application program interfaces.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Clinical Bioinformatics & Exploratory Analytics, as a part of the Clinical Data Science organization, supports drug development and other business use cases across Gilead by providing data analytical, engineering, and visualization solutions to enable scientific and other business exploration and decision-making, including statistical analysis, genomic data processing and analysis, general machine learning and deep learning, and other technical infrastructure.
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Bachelor’s degree required, Masters degree in a quantitative field preferred (Mathematics, Statistics, Computer Science, Data Science, Applied Science, etc). (Tree-based models, ensemble techniques, clustering, deep learning, time series.
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The Global Manufacturing Excellence organization will be the center of excellence in Global Manufacturing under Downstream business line within This Company for Digital transformation, Artificial Intelligence technologies and data science.
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Artificial intelligence, recruitment, machine learning, data science, staffing, ai, community, podcast, Computer Vision, Deep Learning, data engineering, big data, automation, ServiceNow, splunk, digital transformation, executive search, data analytics, cybersecurity, software engineering, software development, and it.
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In this role, you will be part of a team working in a fast-paced, open-ended environment with cutting edge technologies in deep learning and generative AI. You’ll help define and influence how our firm’s data scientists and business teams leverage data and machine learning to improve our processes and products.
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This requires the combination of a deep understanding of statistics/machine learning/other unique methodologies, the technical skills to apply that knowledge to develop and validate models, the creativity to be able to/the curiosity to want to apply it in a unique way, and the results focus and analytical ability to quickly diagnose and fix data integrity concerns as they arise.
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