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

What you'll do

Lead a 0-1 AI transformation for Careem app from personalization perspective.
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; 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 recommendation to communicate state of business, root cause of change in metrics and experimentation results influencing product and business decision
Implement scalable machine learning algorithms that will be used in production on big data.
Embark on exploratory data analysis projects to achieve 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.
Build and deploy retrieval augmented generation systems and other applications of large language models.
What you'll need

10+ years of 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.
Solid experience with Deep Learning Techniques (e.g attention, retrieval models, etc)
3-4 years industrial experience in personalization, recommendation or search is a MUST. Preferably working in a product driven company.
Strong problem solving and coding skills.
Solid knowledge of AB testing, classic ML and DL
Solid understanding of recommendations, ranking and retrieval.
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.

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