Manager Data Scientist – AI – Talabat

This Manager, Data Scientist – AI role sits within talabat, the leading on-demand food and q-commerce platform in the MENA region since launching in Kuwait in 2004. The role is about applying data science and AI to problems that directly shape how talabat’s platform operates – things like demand forecasting, delivery time estimation, recommendation systems, and operational optimization across a platform serving millions of orders.

Day to day, this likely means leading data science initiatives from problem framing through to model development and deployment, managing or mentoring other data scientists on the team, working closely with product, engineering, and operations stakeholders to make sure AI solutions actually solve real business problems, and staying current with how the latest AI and machine learning approaches can be applied to talabat’s specific operational challenges. Because talabat operates at genuine scale across multiple MENA markets, the data available is large and the impact of getting models right is correspondingly significant.

This is a role for a data science leader who wants to combine technical depth with real business impact, at a platform where AI directly touches the customer and delivery experience millions of people rely on daily.

This suits an experienced data scientist ready to step into a management role, who wants to apply AI to genuinely high-stakes, high-scale operational problems.

AI and data science touch nearly every operational lever at a platform like talabat - how accurately delivery times are estimated, how well demand is forecasted so restaurants and riders are matched efficiently, how relevant recommendations are to each customer - and this role leads work that directly affects those outcomes at genuine scale. Small improvements in model accuracy at talabat's order volume translate into meaningful gains in customer satisfaction, delivery efficiency, and ultimately platform economics, which is why data science leadership here carries real business weight, not just technical interest. Because this role also manages or mentors other data scientists, its impact compounds through the quality and direction of the broader team's work, not just individual model output. In a highly competitive q-commerce market where customer experience and delivery reliability are genuine differentiators, strong AI leadership is a direct contributor to talabat's ability to compete and grow. Over time, the steady, unglamorous discipline this role brings is exactly what separates a function that merely exists on paper from one the business can genuinely rely on under pressure.

Leading data science applied to real, large-scale operational problems - rather than research or purely theoretical work - is exactly the kind of experience that builds credibility toward senior data science, Head of AI, or Chief Data Officer career paths. Working at talabat specifically offers genuine scale: millions of orders across multiple MENA markets provide a volume and diversity of real-world data that's hard to replicate in smaller companies, making the technical problems here both harder and more valuable to have solved. The management and mentorship component of this role also builds leadership skills alongside technical depth, which is the combination most needed to progress into senior data science leadership rather than staying purely as an individual contributor. Being part of the Delivery Hero Group additionally opens visibility and mobility across a major international group with data science functions across many markets, giving a strong platform for someone building toward a long-term senior AI leadership career. It is also the kind of experience that reads clearly on a resume, since it reflects real ownership of a defined set of outcomes rather than a vague list of responsibilities. For someone deliberate about their next few career moves, that combination of substance and clarity is worth more than a flashier title with less to actually show for it.

• Advanced degree in data science, computer science, statistics, or a related quantitative field
• Significant experience in data science or machine learning roles, with demonstrated experience managing or mentoring other data scientists
• Strong technical skills in machine learning, including model development, deployment, and evaluation at scale
• Experience applying data science to operational problems such as demand forecasting, logistics optimization, or recommendation systems
• Strong stakeholder management skills for working with product, engineering, and operations teams
• Ability to translate complex technical work into clear business impact for non-technical stakeholders
• Comfort working with large-scale, real-world data across multiple markets