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Data Scientists contribute to projects involving one or more of the following disciplines: Data Science, Applied or Theoretical Machine Learning, Deep Learning, Deep Reinforcement Learning, Physics Inspired ML, Classification Systems, Natural Language Processing, Artificial Intelligence, or Computer Vision.
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Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems, backend, large-scale systems, data science, full-stack.
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Expert knowledge of at least one data science programming language (e.g. Python, R, Julia, etc.) Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Natural Language Processing (NLP): To understand the context and sentiment behind content engagement and social media interactions. NLP libraries such as NLTK or SpaCy for processing text data.
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Develop image processing algorithms for Electro-Optical/Infrared (EO/IR) or Hyperspectral Imagery (HSI) data. Experience with Artificial Intelligence/Machine Learning (AI/ML) applications for image processing.
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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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Hands on experience with Modern Data Warehousing in cloud, Azure Data Factory, Azure Databricks, Pyspark, Azure DevOps, Azure Machine Learning, Azure Data Lake, Power BI, MS SQL Server, SSAS, SSRS, SSIS, Tableau, Alteryx, Natural Language Processing, Scikit-Learn (Classification, Clustering and recommendation system.
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Ring Data Management is seeking a self-directed System Development Engineer to develop and operate our AWS cloud data processing systems. - 3+ years of experience with a modern scripting language such as Python, TypeScript, or Ruby.
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4+ years of Data or Machine learning Science experience working on highly complex problems in a dynamic setting. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
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Proficiency in programming languages such as R, Python, and SQL, with experience in data analysis and machine learning tools like PyTorch, Pandas, scikit-learn, Tensorflow, or similar. Minimum Experience: 2 years of industry experience in dedicated machine learning or data engineering roles, or equivalent to a Master’s degree with strong emphasis in Machine learning.
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Artificial Intelligence, Machine Learning, Cybersecurity, Data Security, Security Analytics, Network Security, Identity and Access Management, IT Risk Management, Behavioral Analytics. It leverages machine learning behavior profiling with predictive risk-scoring algorithms to predict, detect and prevent data breaches, fraud and insider threats.
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Under general supervision of the Sterile Processing Supervisor or Sterile Processing Educator, the Sterile Processing Technician (SPT)II serve with basic knowledge of Sterile Processing techniques/skills and is responsible for decontaminating, operationally checking, assembling, sterilizing, and distributing reusable surgical/clinical instrumentation and implants throughout the organization.
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Solugenix is assisting a client, a prestigious and large investment management company, in their search for a Fixed Income ESG Integration Analyst. Experience working with fixed income data sources such as Bloomberg, and portfolio analysis tools such as Aladdin.
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Causal modeling, NLP, time series, deep learning, etc. Develop and Enhance ML Models: You’ll design, build and deploy sophisticated machine learning models that improve our credit decisioning, fraud detection and other processes.
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PDS consists of eight divisions: Building Services, Code Compliance, Land Development, Long Range Planning, Project Planning, Support Services, Sustainability and the Policy, Outreach and Data division.
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