Manager Data Scientist – AI – Talabat

Talabat, the leading on-demand food and Q-commerce platform launched in Kuwait in 2004 and now part of the Delivery Hero Group, relies increasingly on data science and AI to run its delivery, logistics, and customer experience at scale. This Manager-level Data Scientist role leads AI-focused work within that function, based in Dubai.

The role combines hands-on technical leadership with management responsibility: building and guiding the development of machine learning and AI models that address real operational problems — things like demand forecasting, delivery time estimation, or personalisation — while also managing a team of data scientists and making sure their work connects back to genuine business impact rather than interesting-but-unused models. Translating technical findings into decisions that product, operations, and commercial stakeholders can act on is a core part of the job.

It suits an experienced data scientist with genuine AI and machine learning depth who also wants or already has people-management experience, since the role requires leading a team as much as it requires technical credibility. Experience applying data science in a logistics, e-commerce, or on-demand delivery context is particularly relevant given the nature of Talabat’s business.

Based in Dubai, the role sits inside Talabat’s data science function, giving a manager the scale of a company operating across many markets and millions of daily transactions to apply AI against.

A Q-commerce business like Talabat runs on thousands of small operational decisions happening simultaneously — which orders to batch, how to estimate a delivery time accurately, which item to recommend — and AI models are increasingly what makes those decisions well at scale. This Manager role directly shapes how good those models are and, just as importantly, whether they actually get adopted into real operational and product decisions rather than staying as interesting analysis. Better demand forecasting and delivery estimation directly improve customer experience and operational efficiency, both of which matter enormously to a platform competing on speed and reliability. By managing a team rather than just producing models alone, this role also multiplies its impact, setting the technical direction and quality bar that shapes everything the team ships. As AI becomes a larger differentiator in on-demand delivery competition across the region, the quality of leadership in a role like this has a real, compounding effect on Talabat's competitive position.

Leading AI work inside a company operating at Talabat's scale and transaction volume is a genuinely strong credential, because the problems are real, the data is substantial, and the impact of a model is measurable in actual business outcomes rather than theoretical accuracy scores. Combining technical depth with people management is exactly the profile that senior data science and AI leadership roles require later in a career, and this role is a natural stepping stone toward a Head of Data Science, Director of AI, or Chief Data Officer path for someone who wants to keep progressing in that direction. Working within the wider Delivery Hero Group also means exposure to how AI is applied across multiple markets and brands, broadening perspective beyond a single company's approach. The stakeholder-management side of the role builds the kind of commercial fluency that increasingly separates senior data science leaders from purely technical specialists, since the ability to get AI work actually adopted by the business is often harder than building the model itself. For a data scientist ready to step into management, this role offers both genuine technical scope and real leadership responsibility in the same seat. It also builds the judgement to know when a model is good enough to ship and when it needs more work, a call that only gets harder, and more important, with seniority.

• Strong background in data science, machine learning, or applied AI, with a track record of shipped models
• Experience managing or leading a team of data scientists or machine learning engineers
• Comfortable translating technical model output into clear business recommendations for non-technical stakeholders
• Practical experience applying data science to operational problems, ideally in logistics, e-commerce, or on-demand delivery
• Strong Python and SQL skills, with familiarity in common ML frameworks
• Advanced degree in a quantitative field (Computer Science, Statistics, Mathematics, or similar) or equivalent experience
• Strong stakeholder management skills across product, operations, and commercial teams