Staff Data Scientist (AI & ML) – Dubai, United Arab Emirates | Visa + Salary Insights

📍 Location: ae

🏷 Type: Not specified

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Job Overview

This role is for a Staff Data Scientist (AI & ML) at talabat, a leading on-demand delivery and Q-commerce platform operating across multiple countries in the MENA region. The position focuses on building machine learning systems, Generative AI solutions, and large-scale data-driven decision systems that directly influence customer experience, logistics optimization, and marketplace efficiency. Ideal candidates are senior-level data scientists with 6+ years of experience in production-grade ML, experimentation, and advanced analytics within consumer-facing digital products. You will work closely with product, engineering, and business teams to translate ambiguous problems into scalable AI-driven solutions.

🌍 Work Eligibility & Location

This role is primarily Onsite/Hybrid in Dubai, meaning candidates should be open to relocation or regional presence. Given talabat’s scale across eight countries, international candidates are commonly considered, especially for senior technical roles. Visa sponsorship is highly probable for qualified candidates with strong ML and GenAI experience.

💰 Salary Intelligence

Compensation for a Staff Data Scientist in Dubai’s top-tier tech companies typically reflects high market competitiveness, particularly for candidates with expertise in GenAI, recommendation systems, and production ML pipelines. Total compensation may include performance bonuses and equity-like incentives depending on internal structure.

📊 Role Breakdown

This is a high-impact AI & ML leadership role embedded within talabat’s algorithms team. You will own the full data lifecycle, starting from data generation and logging to modeling, deployment, and experimentation. A major part of the role involves building and scaling machine learning models, recommendation systems, and Generative AI pipelines that enhance personalization, search ranking, and operational efficiency. You will also design A/B testing frameworks and ensure statistical rigor in decision-making processes.

A significant portion of your work involves collaborating with product managers to define success metrics and translating ambiguous business problems into measurable data science solutions. Expect to spend around 30–40% of your time on advanced modeling using tools such as Python, Scikit-learn, XGBoost, TensorFlow, PyTorch, and Hugging Face Transformers. Another 25–30% is dedicated to experimentation design and causal inference. The remaining time focuses on data modeling, stakeholder communication, and improving internal ML infrastructure.

You will also contribute to Generative AI use cases such as content enrichment, automated classification, and intelligent decision support systems that directly impact millions of users across delivery and Q-commerce ecosystems.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly competitive Staff-level AI role requiring deep production experience. Candidates must demonstrate not only modeling skills but also system-level thinking, experimentation design, and cross-functional leadership. Expect strong competition from senior engineers in fintech, e-commerce, and global AI companies.

🚀 Career Impact

This role significantly strengthens your profile in applied AI, recommendation systems, and GenAI engineering. It positions you for future leadership roles such as Principal Data Scientist, AI Architect, or Head of Machine Learning in global tech companies.

📋 Key Responsibilities

You will design and deploy machine learning models that optimize user engagement, delivery efficiency, and marketplace performance. Responsibilities include building scalable pipelines using Python, SQL, and distributed data systems, and developing experimentation frameworks for product validation. You will also work on Generative AI applications such as automated content enrichment and intelligent classification systems. A key responsibility is owning end-to-end analytics, including KPI design, performance measurement, and causal inference. Additionally, you will collaborate with engineering teams to ensure production-grade deployment of ML systems and maintain high reliability in data pipelines.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

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🧠 Fit & Positioning Analysis

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📅 Application Signals

Hiring urgency is typically high for Staff-level AI roles due to ongoing platform scaling and GenAI integration initiatives. Competition is strong, especially from global candidates targeting Dubai’s tech ecosystem. Early application improves visibility significantly, particularly for candidates with strong production ML and experimentation backgrounds.