Senior Data Scientist II - Personalization

• Identify where personalization signals, models, or infrastructure can be shared across Food, Quik, and Shops rather than rebuilt per vertical reducing duplicate work and compounding the value of every experiment.

• Be part of a 0-to-1 AI transformation for the Careem app from a personalization standpoint shaping how generative AI and LLM-based systems augment retrieval and ranking.

• Build a long-term vision for how Careem rethinks customer acquisition and engagement strategies, grounded in data-driven decision-making.

• Drive exploratory analysis to understand user behavior across verticals, identifying new levers to move metrics and building behavioral models that inform product enhancements.

• Shape and influence the ML models and instrumentation that optimize the product experience, surfacing new areas of opportunity and new product directions.

• Provide product leadership through data-driven recommendations communicating the state of the business, root-causing metric movements, and using experimentation results to influence product and business decisions.

• Implement scalable machine learning algorithms that run in production on large-scale data.

• Run exploratory data analysis to better understand user and business phenomena, and to discover untapped areas of growth and optimization.

• Answer complex analytical questions from large datasets to help shape Careem's products and services.

• Define and track key metrics for specific personalization initiatives.

• Design and run randomized controlled experiments (A/B tests), analyze results, and communicate findings to cross-functional teams.

• Continually challenge the status quo investigating new data processing technologies, retrieval architectures, and learning paradigms, and ensuring the team operates at industry-leading standards.

• Build and deploy retrieval-augmented generation (RAG) systems and other applications of large language models within the personalization stack.

What You'll Need:

• 7-10 years of experience in data mining, predictive modeling, time series analysis, machine learning, and Big Data methodologies, including transformation and cleaning of structured and unstructured data.

• Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering, or Computer Science.

• Solid experience with deep learning techniques i ncluding attention mechanisms, retrieval models, and transformer-based architectures (XFY or similar) applied to ranking or recommendation problems.

• Working with or evaluating knowledge graphs, graph neural networks, or graph-based retrieval systems is a strong plus. Careem is actively building toward graph-based retrieval for recommendations.

• 2-4 years of industry experience in personalization, recommendation, or search is a MUST. Preferably gained in a product-driven company operating at scale.

• Strong problem-solving and coding skills.

• Solid knowledge of A/B testing methodology, classical ML, and deep learning.

• Solid understanding of recommendations, ranking, and retrieval systems end-to-end.

• Familiarity with or interest in online/streaming learning systems models that adapt within a session rather than relying solely on batch retraining, is a strong plus.

• Proficiency and demonstrated experience in Python, SQL, Spark, and 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); geospatial data processing skills are a plus.

What We'll Provide You:

We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:

• Work and learn from great minds by joining a community of inspiring colleagues.

• Put your passion to work in a purposeful organization dedicated to creating impact in a region with a lot of untapped potential.

• Explore new opportunities to learn and grow every day.

• Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year.

• Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.

• Data Science

Source: Careem careers page