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The Careem Data Science team’s mission is to drive competitive value from data at scale through the building of AI models to optimize user experiences, decision-making, and operational efficiencies. As one of the tech leaders in this team, you will be at the forefront of fulfilling this mission. You will work with the top data science talent in the region while innovating on our user experience using GenAI.
Responsibilities
- Lead a 0-1 AI transformation for Careem app focusing on personalization.
- Develop a long-term vision on rethinking customer acquisition and engagement strategies, leveraging data for decision-making.
- Conduct exploratory analysis to understand the ecosystem and user behavior, identifying new levers for metric movement and modeling for analysis and product enhancements.
- Shape and influence data/ML models and instrumentation to optimize product experience and generate insights on new opportunities and products.
- Provide product leadership by delivering data-based recommendations that analyze business performance, changes in metrics, and experimentation outcomes, influencing product and business decisions.
- Implement scalable machine learning algorithms for production use with big data.
- Engage in exploratory data analysis projects to better understand phenomena and discover areas for growth and optimization.
- Address complex analytic questions from large datasets to improve Careem’s products and services.
- Help define and monitor key metrics for specific projects.
- Design and execute randomized controlled experiments, analyze data results, and communicate findings with other teams.
- Challenge the status quo while investigating new data processing technologies and ensuring adherence to industry best practices.
- Build and deploy retrieval augmented generation systems and applications of large language models.
Requirements
- Over 10 years of experience in data mining, predictive modeling, time series analysis, machine learning, LLM, and methods related to big data, including transformation and cleaning of structured and unstructured data.
- Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering, or Computer Science.
- Significant experience with Deep Learning Techniques (e.g., attention, retrieval models).
- 3-4 years of industrial experience in personalization, recommendation, or search, preferably in a product-driven company.
- Experience with LLM and GenAI.
- Strong problem-solving abilities and coding skills.
- Solid understanding of A/B testing, classical ML, and DL techniques.
- Familiarity with recommendations, ranking, and retrieval systems.
- Proficiency in Python, SQL, Spark, and Hive.
- Experience with database technologies (e.g., Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).
- Experience with business intelligence and visualization tools (e.g., Tableau, MicroStrategy, ChartIO, Qlik) and geospatial data processing skills is a plus.
