Data Science Manager - Recommendation Systems

Salla; Saudi Arabia; On-site; SAR 480,000 - 720,000; Full time

Job summary

A leading e-commerce platform in Saudi Arabia is seeking a Data Science Manager to spearhead the Recommendation Systems Pod. This role will involve defining the technical roadmap, leading a cross-functional team, and developing state-of-the-art recommendation architectures. The ideal candidate will have extensive experience in applied machine learning, strong leadership skills, and a passion for enhancing user experiences through innovative modeling techniques.

Qualifications

• Experience in leading recommendation systems and personalization efforts.
• Strong background in applied machine learning with a focus on multi-task learning and hybrid ranking.
• Proven ability to manage and mentor technical teams effectively.

Responsibilities

• Define and execute the recommendation roadmap.
• Oversee development of recommendation architectures.
• Manage and mentor a cross-functional team.
• Partner with product teams to align goals.
• Lead the productionization of ML models.
• Define model evaluation and monitoring standards.

Job description

Join us at the ground floor of building the intelligence that powers discovery for millions of shoppers and thousands of merchants across the Middle East.

As the founding Data Science Manager for the Recommendation Systems Pod, you’ll be both an architect and a builder, defining the technical roadmap, assembling the team, and shipping the first generation of models that will shape how users discover, explore, and buy across our platform.

This is a rare zero-to-one opportunity to design the backbone of a large-scale personalization ecosystem in a region with distinct challenges and rich complexity - multilingual search, fast-evolving consumer behavior, and sharp seasonality across GCC markets. You’ll drive measurable topline growth while laying the foundations of a high-performance applied ML organization.

Responsibilities

• Own the Recommendation Roadmap: Define and execute the long-term technical and business strategy for retrieval, ranking, and personalization systems across the platform (search, home feed, and store pages).
• Model Innovation: Oversee development of state-of-the-art recommendation architectures — multi-task learning, sequence-based models, and hybrid (deep + boosted) rankers.
  Drive measurable lift in engagement, CVR, and GMV.
• Lead and Grow the Pod: Manage and mentor a cross-functional team of data scientists, ML engineers, and data engineers. Foster technical excellence, iterative experimentation, and accountability for impact.
• Cross-Functional Leadership:
  Partner with Product, Infra, and Merchant Success to align modeling with business priorities. Translate ambiguous goals into clear, data-backed roadmaps.
• Scalable Deployment & Experimentation:
  Lead productionization of models with real-time feature stores (ClickHouse, Kafka, Spark), and ensure rigorous A/B testing and causal inference for model launches.
• Quality and Governance:
  Define and enforce model evaluation, monitoring, and retraining standards. Maintain consistency in feature usage, labeling, and performance reporting across surfaces.
• Collaboration with GenAI:
  Partner with the GenAI team to infuse recommendation intelligence into conversational shopping experiences and merchant assistants.
• Clear communicator capable of aligning technical and business teams around a common vision.