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Senior Data Scientist II - Personalization

Careem · Doubaï

Senior 🇬🇧 English
Python SQL Spark Hive Hadoop BigQuery Amazon EMR Oracle SAP DB2 Teradata MS SQL Server MySQL Tableau MicroStrategy ChartIO Qlik attention mechanisms transformer architectures graph neural networks A/B testing

Job description

About the role

As a senior technical lead on Careem's Personalization team, you will define how the company approaches hyper‑personalization across Food, Quik, and Shops. You will work with top regional data‑science talent and push state‑of‑the‑art methods such as graph‑based retrieval, transformer architectures, and real‑time learning.

Key responsibilities

  • Own hyper‑personalization use cases across verticals, designing systems that learn user intent in real time and transfer signals across products.
  • Lead exploration of graph‑based retrieval methods, building knowledge‑graph pipelines for candidate generation and ranking at scale.
  • Design and evaluate transformer‑based architectures for sequential and contextual recommendation, moving the ranking stack toward deep, attention‑based models.
  • Drive online/streaming learning systems that adapt within a user session rather than relying solely on batch‑trained models.
  • Identify and share personalization signals, models, and infrastructure across verticals to reduce duplicate work.

Required profile

  • 7‑10 years of experience in data mining, predictive modeling, machine learning, and big‑data methodologies.
  • Advanced degree (PhD or Master) in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering, or Computer Science.
  • 2‑4 years of industry experience specifically in personalization, recommendation, or search at scale.
  • Strong problem‑solving and coding skills with a solid understanding of A/B testing, classical ML, and deep learning.

Required skills

  • Python
  • SQL
  • Apache Spark
  • Hive
  • Hadoop ecosystem (including BigQuery, Amazon EMR)
  • Relational databases (Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL)
  • Business‑intelligence tools (Tableau, MicroStrategy, ChartIO, Qlik)
  • Deep‑learning techniques: attention mechanisms, transformer architectures, graph neural networks
  • A/B testing methodology

What we offer

  • Opportunity to drive impact across the Middle East while learning from top talent.
  • Hybrid work model: 4 days onsite, 1 day remote, plus 30 days of full remote work per year.
  • Unlimited vacation days and flexible remote work from any country.
  • Healthcare benefits and fitness reimbursements (gym, health club, training classes).

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Published 1 month ago

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Careem

Doubaï