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Conversation Designer & NLP Analyst - PNC
United States (Pittsburgh)
Full-time

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. As a Conversation Designer & NLP Analyst within PNC's Strategic Services & Enterprise Architecture organization, you will be based in Pittsburgh, Cleveland, Chicago, Charlotte, or Atlanta. This position is a part of the Intelligent Automation (Cognitive Automation using Digital Virtual Assistants & Conversational AI ) Team. The individual will perform and supervise as lead Virtual Assistant (VA) SME for Conversational design & Natural Language Processing/Understanding (NLP/NLU) design, development, testing, and continuous improvement. This will include critically analyzing the design of conversation flows and training data along with technical code based on the business requirements and other risk factors, including recommendations to address data deficits for improved precision on intent classification of data. Candidate should have a service oriented work ethic while collaborating with various individuals of different levels of experience and stature within PNC. Attention to detail and an analytical mindset is necessary in order to produce complete and accurate results for our service partners. The candidate should have strong business analysis background with conversation, language, grammar proficiency, and a strong level of English language comprehension. The candidate should also have a desire to be involved in all aspects of the VA lifecycle: from blank canvas possibilities through concept prototyping to client discovery, implementation, and maturation.

Key Conversational AI Designer Responsibilities
• Foster user-centered design and research culture, values, and methodologies.
• Support multiple concurrent client projects and a small team of colleagues.
• Garner VA insights and opportunities through workshops, research, and interviews.
• Design business processes led by an understanding of end user wants and needs.
• Develop conversational copy by planning, writing and editing dialogue that creates a more human-like conversational experience.
• Train machine learning models that enable a Virtual Assistant to continuously improve in its understanding of and responses to natural language dialog.
• Review client chat logs, transcripts, recordings and research to improve implementations.
• Work towards continual process improvement and measurement/ benchmarking, with the goal of scaling solutions across business units.
• Uphold and evolve internal knowledge creation, content standards, and best practices.
• Be the “Go-To” person for Conversational Design advice, guidance, and assistance
Key NLP/NLU Designer & Analyst Responsibilities
• Develop an enterprise approach to intents/entities recognition including best practices for utterance-to-intents/entities design, mapping and learning.
• Drive improvements in quality, classification, information structure, and natural language understanding
• Provide in-depth NLP/NLU analysis and design for developing effective Machine Learning models
• Own the creation and governance of methods used to design and optimize models and advise on how to make measurable improvements.
• Work with business and MIS teams to create NLP training and test data: collect utterances, identify patterns & concepts.
• Stay current on advances within the industry in order to disseminate intent education to team members and partners
• Monitor & analyze chat history for continuous improvements
• Setup & enable MIS teams to conduct effective NLU regression testing
• Be the “Go-To” person for NLP/NLU advice, guidance, and assistance

Job Description
• Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.
• Directs the data gathering, data processing and data mining of large and complex datasets.
• Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
• Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.
• Partners with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

Customer Focused
Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.

Managing Risk
Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Competencies
• Data Architecture – Knowledge and ability to create models and standards to govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations.
• Data Mining – Knowledge of tools, techniques and practices in data mining technologies used to acquire essential business information.
• Disruptive Innovation – Knowledge of concepts, principles, and approaches of disruptive innovation; ability to adopt the knowledge into related processes and practices.
• Information Capture – Knowledge of the processes and the ability to identify, capture and document relevant business information in an auditable, organized, understandable and easily retrievable manner.
• Machine Learning – Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
• Modeling: Data, Process, Events, Objects – Knowledge of and the ability to use tools and techniques for analyzing and documenting logical relationships among data, processes or events.
• Prototyping – Knowledge of and ability to implement prototyping disciplines, tools and techniques in evolutionary models within the target environment.
• Query and Database Access Tools – Knowledge of and the ability to use, support and access facilities for extracting and formatting a database management system

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