Morgan Stanley is a global financial services firm and a market leader in investment banking, securities, investment management and wealth management services. With offices in more than 43 countries, the people of Morgan Stanley are dedicated to providing our clients the finest thinking, products and services to help them achieve even the most challenging goals.
As a market leader, the talent and passion of our people is critical to our success. We embrace integrity, excellence, team work and giving back.
The Technology division partners with our business units and leading technology companies to redefine how we do business in ever more global and dynamic financial markets.
Our sizeable investment in technology results in leading-edge tools, software, and systems. Our insights, applications, and infrastructure give a competitive edge to clients’ businesses—and to our own.
Enterprise Technology & Services (ETS) delivers shared technology services for the Firm supporting all business applications and end users. ETS provides capabilities for all stages of the Firm’s software development lifecycle, enabling productive coding, functional and integration testing, application releases, and ongoing monitoring and support for over 3,000 production applications.
ETS also delivers all workplace technologies (desktop, mobile, voice, video, productivity, intranet/internet) in integrated configurations that boost the personal productivity of our employees. Application and end user services are delivered on a scalable, secure, and reliable infrastructure composed of seamlessly integrated datacenter, network, compute, cloud, storage, and database services.
Enterprise System Management (ESM) is a product engineering and development group within the Enterprise Technology & Risk division. It is focused on engineering insight to shrink the Mean-time-to-recover for any IT issues.
We receive nearly 60,000 IT help tickets and 600,000 alerts across our systems every day. Our mission is to increase the knowledge through advanced analytical capabilities through techniques like quality correlation matches of events and interactions. We are building a system to enable our clients to answer complex questions in natural language. You will help us tackle NLP & NLU problems.
This is a demanding role requiring an organized and articulate professional. Capacity to understand requirements from the customer perspective is essential. The ability to influence cross-discipline teams and balance far-reaching stakeholder groups with competing requirements will be key to success.
Conversational Experience Designer define the natural language dialogue that the chatbot uses in order to help improve the overall user experience, making sure that the dialogue feels natural and taking into consideration any technical requirements, business processes, and UI/UX conventions.
Key Responsibilities Will Include
Translating natural language and business language into precise, complex knowledge representations
Design and deployment of models and other structures to identify and fill knowledge gaps in the representation of firm assets, products, services, relations, and processes
Producing conversational diagrams to show the ideal conversational flow, accounting for expected answers and errors, highlighting any UI elements needed.
Working with stakeholders to design and deploy models and ontologies to use for Chat Bot and other AI solutions to improve client experience and improve efficiency, with activities including:
Work to understand current client processes and pain points and help craft the right language for the use case
Write -happy path- transcript for engineers to begin the dialog flow (based on architect/client process diagrams)
Review all wording added to the BPN and make any needed improvements
Classifier Training/FAQs, provide utterances for both goals and FAQs to help improve the chatbot’s understanding
Work with Cognitive Engineers to troubleshoot misses/confusion matrix
Before BPN work commences, high-level review of pre-existing client chat logs, transcripts, recordings and research to grasp user utterances, and (when possible) interview live agents on best practices, industry nuances, and FAQs
After deployment/UAT, high-level review of selected chat logs in order to make additional language recommendations<
Contribute to defining and executing analytics on chats – making sure proper chat analytics are in place and success metrics are available and meaningful, and to ensure there are no language related issues
Create complete copybook to be used for client review and approval
Integrate both unstructured and well-structured data
Assisting with data QA and preparation
Curating, organizing and classifying data with appropriate ontologies
At least 3 years of relevant experience
Experience with knowledge bases
Proficiency in data analysis, semantic modeling, knowledge and ontology engineering
Understanding of complex data models and technologies
Excellent written and verbal communication
Strong attention to detail
Bachelor Degree in a relevant discipline
Nice to have
Strong interpersonal skills
Ability to influence cross-discipline teams
Ability to work as part of a start-up team within a larger company
Capacity to understand requirements from customer perspective
Degree in Library Science, Information Science, Information, Psychology, information Systems. Management Information Systems or other related discipline
Knowledge of French and English is required.
Level of experience (years):
Mid Career (2+ years of experience)
About Morgan Stanley
Preeminent financial advisor