
Careem
Senior Data Scientist II
- Permanent
- Dubai, United Arab Emirates
- Experience 5 - 10 yrs
Job expiry date: 05/06/2026
Job overview
Date posted
21/04/2026
Location
Dubai, United Arab Emirates
Salary
Undisclosed
Compensation
Job description
The Senior Data Scientist II role at Careem in Dubai, United Arab Emirates is part of a high-impact AI and data science organization focused on building the Everything App for the greater Middle East, spanning mobility, food delivery, groceries, payments, and digital services. The role is central to Careem’s AI transformation journey, focusing on applying advanced machine learning, deep learning, and generative AI techniques to improve personalization, customer experience, operational efficiency, and business decision-making at scale. The Senior Data Scientist II is responsible for designing and implementing scalable machine learning systems deployed in production on large-scale big data platforms using Python, SQL, Spark, Hive, and distributed data technologies. The role involves building predictive models, recommendation systems, ranking and retrieval models, and personalization algorithms that directly influence customer acquisition, engagement strategies, and product optimization. The position requires deep expertise in exploratory data analysis to understand user behavior, ecosystem dynamics, and to identify new opportunities for growth and optimization. The role includes defining and tracking key performance metrics, analyzing complex datasets, and delivering data-driven insights that influence product and business strategy. The data scientist will design and run randomized controlled experiments (A/B testing), analyze results, and communicate findings to cross-functional teams. A key responsibility includes building and deploying retrieval-augmented generation systems and other large language model-based applications to enhance AI-driven product experiences. The role also involves shaping ML instrumentation, influencing model design, and driving insights that improve product outcomes. The position requires continuous exploration of new technologies, adherence to industry best practices, and leadership in applying AI innovations to real-world business problems in a fast-scaling product environment.
Required skills
Key responsibilities
- Lead the development of AI-driven personalization models to support Careem’s 0–1 AI transformation across the super app ecosystem
- Conduct exploratory data analysis to understand user behavior, ecosystem dynamics, and identify opportunities for growth and product optimization
- Design, build, and deploy scalable machine learning models including recommendation systems, ranking systems, and predictive models on large-scale production data
- Develop and implement retrieval-augmented generation (RAG) systems and large language model applications to enhance product intelligence and automation
- Define key metrics for business and product performance and ensure continuous tracking, monitoring, and optimization of these metrics
- Design and execute randomized controlled experiments (A/B testing), analyze results, and communicate insights and recommendations to product and business teams
- Answer complex analytical questions using large-scale structured and unstructured datasets to support decision-making and product strategy
- Provide data-driven product leadership by communicating insights on business performance, root cause analysis of metric changes, and experimentation outcomes
Experience & skills
- Possess 7–9 years of experience in data mining, predictive modeling, machine learning, time series analysis, and big data methodologies
- Demonstrate advanced academic background in Physics, Statistics, Mathematics, Engineering, Computer Science, or related quantitative discipline
- Demonstrate strong experience in deep learning techniques including attention mechanisms and retrieval-based models
- Demonstrate at least 1–2 years of industrial experience in personalization, recommendation systems, or search systems in a product-driven company
- Demonstrate strong programming and problem-solving skills using Python, SQL, Spark, and distributed data processing frameworks
- Demonstrate solid understanding of A/B testing, machine learning, deep learning, recommendation systems, ranking, and retrieval methodologies
- Demonstrate experience working with big data technologies such as Hadoop, BigQuery, Amazon EMR, Hive, Oracle, DB2, Teradata, MS SQL Server, or MySQL
- Demonstrate familiarity with business intelligence and visualization tools such as Tableau, MicroStrategy, ChartIO, or Qlik (plus geospatial data processing is an advantage)