Data Science Manager

Data Science Manager — Dubai, UAE

Key responsibilities

• Define and execute the data science roadmap aligned to business priorities in analytics, AI, and digital transformation
• Lead and develop a high-performing team across data science and (where relevant) data engineering, setting clear standards for quality, delivery, and ownership
• Partner with business leaders to identify high-value use cases and translate them into well-scoped initiatives with clear success metrics
• Deliver end-to-end ML solutions: problem framing, feature engineering, model development, validation, deployment, and monitoring
• Drive AI enablement by building reusable components, templates, and best practices that accelerate delivery across teams
• Ensure strong governance across model risk, documentation, privacy, compliance, and cost efficiency
• Collaborate closely with data platform teams to ensure scalable ingestion, processing, and secure access to trusted data
• Communicate clearly with senior stakeholders through concise reporting, dashboards, and outcome-focused updates
• Desired profile
• Proven experience leading data science teams and delivering production ML solutions at scale
• Strong applied ML background (e.g., classification, churn prediction, time series, forecasting, recommendation, NLP, anomaly detection)
• Strong data engineering literacy and ability to work closely with platform teams on pipelines, quality, and performance
• Comfortable operating in fast-moving, stakeholder-heavy environments with clear prioritisation and delivery cadence
• Strong Python and SQL, with modern analytics engineering and orchestration exposure
• Experience with modern lakehouse / cloud stacks is highly preferred (e.g., Databricks, Delta/Iceberg, dbt, Airflow, Unity Catalog, Azure/AWS/GCP)
• Strong visualisation and storytelling skills (e.g., Power BI) with an outcomes-first mindset

Skills

• Nice to have
• Domain experience in shipping, logistics, supply chain, or similarly operational industries
• Experience building group-wide data platforms or intelligence products
• Exposure to geospatial/spatial analytics and operational optimisation use cases