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Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
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Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value; Using natural language understanding (NLU) and sentiment analysis.
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Understanding of Large Language Models such as Bard and/or OpenAI and NLG solutions; We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
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Working in Contact-Center-as-a-Service and/or Conversational AI development, with a track record of delivering successful projects; and, Working closely with stakeholders across the organization to ensure that Contact Center and Conversational AI solutions are aligned with company goals and values, and meet regulatory requirements.
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Address sub-standard work or work that does not meet firm's/client's expectations. As a Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution.
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Directing associates / senior associates through coaching, providing feedback, and guiding work performance. Leading and contributing to development of proof of concepts and/or pilots for clients while working in cross-functional teams.
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Act to resolve issues which prevent the team working effectively. Understanding or hands on experience with Lex, Nuance Mix, Dialog Flow, AWS and Google Cloud, R, Power BI, Tableau, Alteryx; Understanding or experience with Contact Center as a service providers such as Nice, Nuance or Genesys and leading contact center transformation projects.
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Using chatbot development frameworks, such as RASA or Microsoft Bot Framework; Applying experience with cloud platforms, such as AWS, Google Cloud, or Microsoft Azure; Understanding or experience with conversational AI platforms, such as Google Dialogflow, Amazon Lex, IBM Watson, Microsoft Azure hyper-scalers.
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Linguistics, Computer and Information Science, Engineering. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology.
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You'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights. Understanding of data privacy and security regulations and best practices.
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Developing and implementing Contact Center AI & Conversational AI strategies that drive user engagement and adoption, as well as business growth and revenue; Relational storage (SQL), Non-relational storage (NoSQL), RASA bot framework, LUIS, Azure.
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Developing AI solutions for multilingual audiences; To help us achieve this we have the PwC Professional; our global leadership development framework. Leading the design and development of Contact Center AI solutions and Conversational AI solutions that improve customer engagement and satisfaction, reduce customer service costs, and increase operational efficiency.
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Managing the end-to-end AI development lifecycle, from ideation and design to testing, deployment, and maintenance; PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation and more.
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For positions based in San Francisco, consideration of qualified candidates with arrest and conviction records will be in a manner consistent with the San Francisco Fair Chance Ordinance. Managing daily operations of a global data and analytics team on client engagements, review developed models, provide feedback and assist in analysis.
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