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Expert Understanding of technologies used in the IVR and telephony: Dialogue Design tools, Chat bot, Text to Speech, Speech Recognition, Toll Free Number Engineering, Automatic Call Distribution, Natural Language Processing.
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Interested in Text analytics, Natural Language processing, Classification and Clustering. Solid understanding of data management concepts - data processing, analytics, machine learning and visualization.
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Data Processing and Indexing: Skilled in uploading, processing, and indexing documents to make data searchable and retrievable through natural language queries. Specializes in leveraging Microsoft Azure services, including Azure Cognitive Search and Azure OpenAI, to create sophisticated chat interfaces that allow users to interact with their own data in natural language.
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Experience working on natural language processing. The Senior Data Scientist NLP and GenAI role involves designing and implementing NLP algorithms, small and/or large language models to understand, interpret, and analyze natural language.
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Azure OpenAI Integration: Expert in integrating Azure OpenAI large language models to develop ChatGPT-style applications, allowing for natural language interactions with complex datasets.
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Expert understanding of Collaboration Tools such as Miro, Azure DevOps, SharePoint, Microsoft Teams, Microsoft Powerpoint, Microsoft visio. Expert understanding of Agile Methodologies, Preferably certified Agile Product Owner.
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Experience with building and leading high-performing teams IT WOULD BE NICE IF YOU HAVE: Experience in the talent acquisition, recruiting and/or staffing industry Experience with natural language processing, classification, matching and engagement tools.
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Expert understanding of Genesys IVR, IVA, Voice Bot, Chat bot. Serve as Product Owner for IVR Applications. Expert Understanding of benefits of IVR: Call Containment, Call Misdirects, User experience, Cost Savings, Average Handle/Call Time.
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Demonstrated 4+ years' hands-on experience with Python, SQL, Natural Language Processing (NLP), Large Language Model (LLM), TensorFlow/Pyspark/ or Keras is highly preferred.
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Ensure that post production / smoke testing is conducted and issues are escalated and resolved. The UAT Coordinator will be responsible for communication between testers, IT, and appropriate stakeholders; ensure that test cases are loaded in the QA/Azure tool correctly and executed in a timely manner; and manage defect tracking and resolution.
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Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques. Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models.
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