Opportunity at
CareemSenior Data Scientist II - Personalization
Careem is hiring a Senior Data Scientist II for its Personalization team, which works inside Data Science and determines what each user sees and in what…
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About This Role
Careem is hiring a Senior Data Scientist II for its Personalization team, which works inside Data Science and determines what each user sees and in what sequence across Food, Quik and Shops. The job is full-time and on site in Dubai, with four office days a week. The group develops live recommendation and ranking engines that pick up behaviour in one vertical and reuse it elsewhere. As a senior technical…
Job Description
Careem is hiring a Senior Data Scientist II for its Personalization team, which works inside Data Science and determines what each user sees and in what sequence across Food, Quik and Shops. The job is full-time and on site in Dubai, with four office days a week. The group develops live recommendation and ranking engines that pick up behaviour in one vertical and reuse it elsewhere.
As a senior technical lead, the data scientist would own personalisation work across Food, Quik and Shops and help set the company's approach at regional scale. Responsibilities include leading research into graph-based retrieval for recommendations, including knowledge-graph pipelines for candidate generation and ranking, and designing transformer models for sequential and context-aware recommendations. The role also pushes toward streaming learning that adapts during a session.
Other tasks include finding where signals and infrastructure can be reused across verticals, designing and reading randomised experiments, setting metrics for each initiative, and carrying out exploratory analysis to uncover growth levers. The data scientist would also create retrieval-augmented generation systems and other large language model tools inside the personalisation stack, and share findings with cross-functional teams.
The posting asks for at least two to four years of industry experience in personalisation, recommendation or search, plus a wider background of roughly seven to ten years in data mining, predictive modelling, machine learning and big data. A postgraduate degree in a numerate field, for example physics, statistics, maths, engineering or computing, is expected. Candidates should know A/B testing, deep learning and end-to-end recommendation and ranking well, and be fluent with Python, SQL, Spark and Hive tooling.
Responsibilities
- Take charge of personalisation work for Food, Quik and Shops
- Lead research into graph-based retrieval and knowledge-graph pipelines
- Design and evaluate transformer architectures for ranking and retrieval
- Plan and analyse A/B tests and share results with teams
- Find personalisation models and infrastructure that can be reused across verticals
- Build RAG systems and other LLM applications in the personalisation stack
Requirements
- Two to four years of industry experience in personalisation, recommendation or search
- Solid deep learning background, including attention mechanisms and transformer models for ranking
- Solid grasp of A/B testing, classical machine learning and deep learning
- End-to-end understanding of recommendation, ranking and retrieval systems
- Working command of Python, SQL, Spark and Hive
- Postgraduate study in a numerate subject like physics, statistics, maths, engineering or computing
Qualifications
- Background with knowledge graphs, GNNs or graph-driven retrieval
- Familiarity with online or streaming learning systems
- Experience with BI tools such as Tableau or Qlik, plus geospatial data work
Core Skills
Benefits
- Four office days a week and one day from home
- Work remotely from abroad for up to 30 days a year, and vacation days are unlimited
- Healthcare cover and fitness reimbursements for gyms, health clubs and classes
- Chances to learn and develop alongside a community of colleagues
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the role based?
Dubai, on site, with four office days a week and one day from home for full-time staff.
What salary is offered?
The posting does not specify a salary.
What experience is a must-have?
At least two to four years of industry experience in personalisation, recommendation or search is described as a must.
What degree is expected?
A postgraduate degree in a numerate field, for example physics, statistics, maths, engineering or computing.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.
