AI Business Analyst

Our client is an international technology solutions provider delivery cutting edge solutions to their clients.

We are recruiting an experienced technology business analyst to join their Abu Dhabi team.

Candidates should have experience of conversational and generative AI solutions using LLM and associated techniques.

Role Summary

• Conduct in-depth analysis of client requirements; translate business needs into technical specifications and make recommendations for delivering scalable solutions related to conversational AI and LLM projects.
• Develop and present reports, dashboards, and visualizations to communicate insights to stakeholders.
• Design conversational flows for leading vendor products.
• Produce LLDs.

Mandatory Skills & Experience

• 7 – 10 years’ experience as a technology business analyst with a minimum of 2 years’ experience in AI.
• Experience with AI and NLP technologies, particularly in the context of conversational interfaces and LLMs.
• Experience in data analysis, AI analytics, conversational AI or natural language processing - Large Language Models, NLUs, retrieval-augmented generation and generative AI concepts.
• Knowledge of machine learning concepts, NLP techniques, and AI model valuation metrics.
• Familiarity with conversational AI platforms, chatbot frameworks, voice recognition technologies, and customer interaction analytics tools.
• Proficient experience of BPMN, model entity and related techniques to enhance delivery.
• Working knowledge of Amelia, Omelia, Kore and / or related Conversational AI products are a strong advantage.
• Proficiency in data analysis tools and languages such as Python, R, SQL, or related platforms for analyzing and visualizing large datasets.

Education

• Bachelor’s degree in Computer Science, Data Science, Information Technology

Candidate Profile

• Currently living in the United Arab Emirates – must be able to work in Abu Dhabi.
• Fluent in English.
• Professional appearance, interpersonal, communication and presentation skills to articulate complex data findings and insights to both technical and non-technical stakeholders.