Overview: We are looking for a passionate and empathetic Technical Business Analyst to join an expanding team to support the evolution of our cutting-edge conversational AI solutions, using LLM and associated techniques to drive faster delivery and more robust solutions to our clients.
As a Technical Business Analyst at Bell Integration, you will be responsible for conducting in-depth analysis of Clients' requirements for conversational AI interactions and helping to drive insights and providing recommendations for delivering stable and maintainable solutions.
Using LLMs and Generative AI you will also help deliver Bell's AI solutions to the AI & Data Practice that will support faster delivery to the client.
You will work in the AI & Data Practice as a member of the solutions team and ensure the optimal performance & delivery of our conversational AI applications (Currently Amelia) and the use of generative AI to improve customer & developer low-code experience.
Work Environment: The Technical Business Analyst at Bell will work in a dynamic and collaborative environment with opportunities for professional growth and skill development.
The role may involve collaboration with cross-functional teams, engagement with external partners or clients, and participation in AI-related industry events or conferences.
Bell Integration is committed to fostering a diverse and inclusive workplace and encourages individuals from all backgrounds to apply.
Responsibilities: Conversational AI Solutioning: Translate business needs into technical specifications for conversational AI systems and LLMs.
Use Generative AI & LLMs to enhance customer feedback and provide insights into their data.
Use Generative AI & LLMs to shorten delivery times and reduce the cost of build by helping to reduce the development effort (moving to low-code).
Utilize data analysis tools and techniques to review and analyze conversations to improve retention rates.
Identify NLU Routes / Intents for use in conversations to support better estimating.
Model conversational flows through BPMN or other techniques.
Model Entity usage and prediction of the tools understanding of the conversation.
Facilitate communication between technical and non-technical stakeholders.
Generate Actionable Insights: Collaborate with cross-functional teams to identify opportunities for improving the conversational AI user experience and driving business impact.
Develop and present reports, dashboards, and visualizations to communicate insights to stakeholders.
Stay informed about the latest advancements in conversational AI technologies and industry best practices.
Contribute to the continuous improvement of the conversational AI applications by providing feedback and recommendations for future developments.
Participate in the development of AI training data sets and annotation guidelines to improve the accuracy and relevance of the AI models.
Stakeholder Collaboration: Collaborate with the customer success team and assist in addressing customer feedback, inquiries, and issues related to conversational AI interactions.
Engage with internal stakeholders to gather requirements, understand business objectives, and align AI strategies with organizational goals.
Qualifications: Bachelor's degree in Computer Science, Data Science, Information Technology, or related subject is required.
Experience with AI and NLP technologies, particularly in the context of conversational interfaces and LLMs.
Knowledge of Large Language Models, retrieval-augmented generation, and generative AI concepts.
Experience in data analysis, AI analytics, or related roles, preferably within the context of conversational AI or natural language processing.
Knowledge of machine learning concepts, NLP techniques, and AI model valuation metrics is desirable.
Familiarity with conversational AI platforms, chatbot frameworks, voice recognition technologies, and customer interaction analytics tools.
Strong analytical, problem-solving, and critical thinking skills with a keen attention to detail.
Excellent communication and presentation skills to articulate complex data findings and insights to both technical and non-technical stakeholders.
Ability to work collaboratively in a cross-functional environment and adapt to evolving requirements and priorities.
Comfortable with proficiency in data analysis tools and languages such as Python, R, SQL, or related platforms for analyzing and visualizing large datasets is a plus.
Knowledge of Generative AI in the Conversational AI area is a plus.
Knowledge of software development methodologies and agile principles is beneficial.
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