Senior Manager Data Science

Jex Recruitment | Connecting top talent with leading companies; Dubai; On-site; AED 350,000 - 700,000; Full time

Job summary

I'm currently supporting a leading UAE bank with the appointment of a Senior Manager - Data Science to join its growing Data function. This hands-on leadership role focuses on delivering high-impact Data Science and Machine Learning solutions across Retail, Corporate Banking, Risk, Credit and Operations.

The successful candidate will translate complex business problems into scalable, production-ready ML solutions that deliver measurable outcomes, owning the full ML lifecycle from feature

Qualifications

• 7+ years of Data Science / ML experience.
• Strong Python and ML development skills.
• Experience with MLOps and productionizing ML models.
• Familiarity with Generative AI / LLMs.
• Experience building cloud-based ML pipelines (Azure / AWS).
• CI/CD and modern ML engineering practices.
• Proven experience leading teams / cross-functional squads.

Responsibilities

• Own the full ML lifecycle from feature engineering to deployment.
• Monitor model performance and data drift; iterate on improvements.
• Translate complex business problems into scalable ML solutions.

Skills

Data science

Python

ML development

MLOps

Generative AI

CI/CD

Team leadership

Tools

Azure

AWS

Job description

I'm currently supporting a leading UAE bank with the appointment of a Senior Manager - Data Science to join its growing Data function.

This is a hands-on leadership role focused on delivering high-impact Data Science and Machine Learning solutions across areas including Retail Banking, Corporate Banking, Risk, Credit and Operations. The successful candidate will take complex business problems and translate them into scalable, production-ready ML solutions that deliver measurable business outcomes.

We're looking for someone with strong experience across:

• 7+ years' Data Science / Machine Learning experience
• Advanced Python & ML development
• MLOps and productionising ML models
• Generative AI / LLMs
• Cloud-based ML pipelines - Azure / AWS
• CI/CD and modern ML engineering practices
• Experience leading teams / cross-functional squads

You should be comfortable owning the full ML lifecycle - from feature engineering, model selection and validation through to deployment, performance monitoring and data-drift management.