Careem - Senior Data Scientist II - Personalization
Requirements
• 6-8 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 including 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 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.
Responsibilities
• Drive real-time, cross-vertical personalization: Own hyper-personalization use cases across Food, Quik, and Shops designing systems that learn a user's intent and preferences in real time and transfer that signal across verticals, so a user's behavior on one product makes every other product smarter. • Advance graph-based retrieval: Be a technical lead on Careem's exploration of graph-based retrieval methods for recommendations including evaluating and building knowledge graph pipelines that power candidate generation and ranking at scale. • Build next-generation ranking models: Design and evaluate transformer-based architectures (XFY) for sequential and contextual recommendation moving Careem's ranking and retrieval stack beyond classical ML toward deep, attention-based models. • Pioneer real-time learning: Push toward online/streaming learning systems that adapt to user behavior within a session, not just from batch-trained models refreshed on a daily cadence. • Build for cross-learning: 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.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT