Data Scientist / AI Engineer

About the role

Join Emirates Group Analytics Centre of Excellence in Dubai, where data, AI and innovation drive decisions for a leading aviation and travel brand. As a Data Scientist/AI Engineer you will tackle complex commercial, operational and customer challenges using machine learning, generative AI and agentic AI to deliver measurable business impact.

Key responsibilities

• Design, develop and deploy machine‑learning, GenAI and agentic AI solutions that improve business performance.
• Analyse large structured, semi‑structured and unstructured data sets to extract insights and identify opportunities.
• Build predictive, prescriptive and optimisation models across commercial, operational and customer domains.
• Collaborate with stakeholders to translate business problems into scalable data‑science projects.
• Create visualisations, dashboards and analytical tools to support decision‑making.
• Contribute reusable libraries, frameworks and production‑ready assets for the analytics community.
• Apply experimentation techniques such as A/B testing, segmentation and customer analytics.
• Work with engineers, analysts and product teams in an agile environment to deliver AI‑powered products and intelligent automation.

Required profile

• MSc or PhD in Data Science, AI, Machine Learning, Mathematics, Statistics, Operations Research, Computer Science, Economics or a related quantitative discipline.
• 2‑4+ years of experience delivering advanced analytics, machine‑learning or AI solutions in a commercial setting.
• Strong problem‑solving mindset and ability to communicate technical concepts to non‑technical audiences.

Required skills

• Proficiency in Python and SQL.
• Experience with Spark or other distributed data‑processing frameworks.
• Hands‑on experience developing and deploying ML, LLM, GenAI and agentic AI models.
• Familiarity with AI engineering practices: model deployment, monitoring, evaluation, prompt and context engineering.
• Knowledge of MLOps workflows, Git, Docker and CI/CD pipelines.
• Ability to build reusable libraries, APIs and production‑grade data‑science solutions.