Careem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.
Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.
We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.
About the team
The Careem Data Science team’s mission is to drive competitive value from data at scale through building AI models to optimize user experiences, decision making, operational efficiencies, and lead the region’s AI ecosystem. As one of the leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with and leading the top data science talent of the region, leveraging AI to solve the region’s day-to-day problems, through state-of-the-art machine learning, optimization, deep learning, and RL models, that are deployed on top of our own in-house AI platform, serving users in real-time.
What you'll do
- Build a long-term vision on how we can rethink our customer acquisition and engagement strategies, leveraging data in our decision making.
- Drive exploratory analysis to understand the ecosystem, user behavior, identify new levers to help move metrics, and build models of user behaviors for analysis and product enhancements.
- Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.
- Provide product leadership by sharing data-based recommendations to communicate state of business, root cause of change in metrics, and experimentation results influencing product and business decisions
- Implement scalable machine learning algorithms that will be used in production on big data.
- Embark on exploratory data analysis projects to achievea better understanding of phenomena as well as to discover untapped areas of growth and optimization.
- Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.
- Help define and track the appropriate key metrics for specific projects.
- Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams.
- You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.
What you'll need
- Experience in data mining, predictive modeling, time series analysis, machine learning, Big Data methodologies, transformation and cleaning of both structured and unstructured data.
- Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
- Strong problem solving and coding skills.
- Solid knowledge of and experience with marketplace problems in ride hailing and delivery services.
- Solid knowledge of AB testing, classic ML and DL
- Solid understanding of recommendations, learning to rank, uplift modeling and matching problems.
- Fluency in English along with excellent oral and written communication skills.
- Proficiency and demonstrated experience in: Python, SQL, Spark, Hive.
- Demonstrated experience with database technologies (e.g. Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).
- Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik) along with geospatial data processing skills is a plus.
- Knowledge of Agile methodologies.
