What you'll do
- Be part of 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
- 4-6 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)
- 1-2 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.