Data Scientist – AI

About the Role

Join Miral Destinations as a dedicated Data Scientist within their specialized AI team, focused exclusively on projects advancing Miral Destination initiatives. Your role involves analyzing destination data, developing and refining AI and machine learning models, and delivering practical insights that drive business goals. You will work closely with the ML Ops Engineer to transition models from experimental phases into production and report directly to the Senior Manager AI to ensure alignment with the strategic AI roadmap.

Key Responsibilities

• Examine Miral Destination datasets to identify patterns and opportunities that inform strategic decisions for the destination.
• Create, train, and optimize AI and machine learning models tailored specifically for Miral Destination applications.
• Build Retrieval-Augmented Generation (RAG) pipelines, manage vector databases, and develop large language model (LLM) solutions on Databricks tailored to Miral Destination needs.
• Produce clear insights and compelling visualizations that support core business objectives.
• Collaborate with ML Ops engineers to operationalize models, ensuring models are production-ready, continuously monitored, and maintained.
• Convert stakeholder requirements, communicated via the Senior Manager AI, into precise data science deliverables.
• Ensure all work adheres to enterprise AI architecture, governance, security, and data management policies governed by the AI & Data organization.
• Maintain rigorous standards for data quality, model performance, governance, and responsible AI practices across all engagements connected to Miral Destination.
• Engage with cross-functional teams in AI, Data Engineering, Business Intelligence, and Enterprise Data across DTD to leverage shared tools, platforms, and best practices.

Qualifications and Experience

• 3 to 5 years of professional experience in Data Science, Machine Learning, or Advanced Analytics.
• Proven track record in progressing AI models from analysis through to deployment and production monitoring.
• Strong expertise in data analysis, statistical modeling, and machine learning techniques.
• Hands-on proficiency with Python programming and Databricks platform, including MLflow for model lifecycle management.
• Experience with AI model construction, fine-tuning, and evaluation methodologies.
• An understanding of Retrieval-Augmented Generation (RAG), large language models (LLMs), and vector database concepts.
• Skillful in data storytelling—translating complex data analyses into clear, impactful business insights.
• Collaborative experience working alongside ML Ops to deploy and maintain AI models effectively.

Educational Background

A Bachelor’s or Master’s degree in Data Science, Artificial Intelligence, Statistics, Computer Science, or a closely related discipline is required.