Data Scientist - AI Transformation Specialist

Unlock Your Potential in AI Transformation

Careem is revolutionizing the Everything App for the Middle East, making it easier to move around, order food and groceries, manage payments, and more. Our purpose is to simplify and improve lives by building an awesome organisation that inspires. Since its inception, Careem has created earnings for over 2.5 million Captains, simplified the lives of over 70 million customers, and built a platform for the region's best talent to thrive and for entrepreneurs to scale their businesses.

The 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 tech leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with top data science talent while innovating on our user experience using GenAI.

Be part of a groundbreaking AI transformation for the Careem app from personalization perspective. Build a long‑term vision on how we can rethink customer acquisition and engagement strategies leveraging data in our decision making. Drive exploratory analysis to understand the ecosystem, user behavior; identifying 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 the 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 achieve a 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 shape products and services in a better way. Help define and track key metrics for specific projects. Design and run randomized controlled experiments, analyze the resulting data and communicate results with other teams.

You will continually investigate new data processing technologies and seek to ensure that we follow industry best practices. Build and deploy retrieval augmented generation systems and other applications of large language models.

We are seeking highly skilled professionals with extensive experience in data mining, predictive modeling, time series analysis, machine learning, Big Data methodologies, data transformation and cleaning, both structured and unstructured data.

• At least 5-6 years of experience in data‑related fields.
• Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
• Solid experience with Deep Learning techniques (e.g., attention, retrieval models, etc.).
• 1-2 years industrial experience in personalization, recommendation or search.
• Strong problem‑solving and coding skills.
• Solid knowledge of AB testing, classic ML and DL.
• Solid understanding of recommendations, ranking and retrieval.
• Proficiency in Python, SQL, Spark, Hive.
• Strong communication skills.
• Experience with database technologies (Hadoop, Big Query, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).
• Experience with business intelligence and visualisation tools (Tableau, Micro Strategy, Chart
  
  IO, Qlik).
• Geospatial data processing skills is a plus.

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

• 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 untapped potential.
• Explore new opportunities to learn and grow every day.
• Enjoy flexible working arrangements, including 4 days a week in office and 3 days from home.
• Access healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.