Careem
Director of Data Science (Machine Learning)
- Permanent
- Dubai, United Arab Emirates
- Experience 10 - 15 yrs
Job overview
Date posted
10/11/2025
Location
Dubai, United Arab Emirates
Salary
AED 60,000 - 100,000 per month
Compensation
Comprehensive package + relocation
Experience
10 - 15 yrs
Seniority
Director
Qualification
Bachelors degree
Expiration date
25/12/2025
Job description
The Director of Data Science (Machine Learning) at Careem leads the central Machine Learning and Data Science organization, comprising over 30 members responsible for scaling applied AI innovation across the Everything App. The role defines and executes Careemâs multi-year AI strategy, integrating machine learning systems into all business verticals to deliver measurable ROI and strategic differentiation. This leader oversees the design, development, and deployment of production-grade ML systems, including data collection, feature engineering, model training, deployment, and monitoring. The position involves driving standardization, scalability, and automation through MLOps, enabling faster iteration cycles. The Director plays a pivotal role in embedding AI into Careemâs platformâenhancing personalization, recommendations, search, and fraud detection systems while leading innovation in Generative AI and Large Language Model applications. This position requires cross-functional collaboration with Engineering, Product, and Data teams, ensuring robust infrastructure for data pipelines, model serving, and retraining. The role also entails representing Data Science in executive forums, shaping AI investment priorities, and partnering with academia to advance applied AI capabilities across the region. The Director will foster a culture of inclusion, technical excellence, and experimentation, mentoring emerging leaders and building a team that drives measurable product impact and customer experience improvements.
Required skills
Key responsibilities
- Define and execute the vision and long-term strategy for Data Science and Machine Learning across all Careem verticals.
- Partner with product, engineering, and business leaders to identify and prioritize AI opportunities with measurable ROI.
- Drive standardization, scalability, and platformization across ML systems to accelerate innovation and delivery.
- Evangelize AI across Careem to align investments with strategic priorities.
- Build, lead, and inspire a high-performing team of over 30 data scientists and ML engineers distributed across multiple geographies.
- Foster a culture of inclusion, ownership, and innovation within the Data Science organization.
- Oversee design, development, and deployment of end-to-end ML systems covering data collection, feature engineering, training, and production monitoring.
- Collaborate with engineering teams to ensure robust ML infrastructure for large-scale model training and serving.
- Define and manage the AI technical roadmap and ensure its alignment with business goals.
- Lead Generative AI and LLM research and application development to maintain Careemâs competitive edge.
- Champion MLOps automation to shorten experimentation-to-production cycle time.
- Ensure measurable product and business impact through ML integrations in user-facing features such as personalization and ranking.
- Develop frameworks for evaluating AI-driven product outcomes and impact measurement.
- Represent Data Science leadership in strategic company forums to influence priorities and investment decisions.
- Collaborate with platform, analytics, and data teams to align architecture and tooling strategies.
- Establish partnerships with research institutions to drive AI innovation and thought leadership in the region.
Experience & skills
- Minimum of 10 yearsâ experience in Data Science, Machine Learning, or Applied AI roles, including 5 years in senior leadership.
- Proven record of deploying and scaling ML systems in production for large-scale consumer platforms.
- Advanced degree in Computer Science, Machine Learning, or a closely related field.
- Demonstrated ability to translate complex ML concepts into strategic business outcomes.
- Experience leading distributed technical teams of significant size and complexity.
- Proficiency in end-to-end ML development including data preparation, model training, deployment, and monitoring.
- Strong understanding of MLOps, automation pipelines, and cloud-based ML infrastructure.
- Proven expertise in Generative AI and Large Language Models for product applications.
- Experience applying ML in areas such as personalization, recommendation systems, search optimization, marketplace dynamics, and fraud prevention.
- Strong stakeholder management and communication skills with both technical and non-technical audiences.
- Ability to define success metrics and performance measurement frameworks for AI initiatives.
- Deep passion for product-oriented AI and building human-centered, data-driven experiences.
