Senior Data Scientist Recommendation Systems Pod📣 إعلان

منذ ساعتين تقريبا

	نوع العقد	دوام كامل
	طبيعة الوظيفة	بالموقع
	الموقع	مكة المكرمة

وصف الوظيفة

About the Role

Salla is seeking a Senior Data Scientist to join the Recommendation Systems Pod. This role is based in Makkah, Makkah Province, and involves a full-time work commitment. The position focuses on building the intelligence that powers product discovery for millions of shoppers and thousands of merchants across the Middle East, directly impacting the company's topline through the design and execution of large-scale personalization models.

Role Context and Impact

This is an opportunity to shape the next generation of commerce AI in a high-growth market with diverse user and merchant behaviors across the GCC. The Senior Data Scientist will lead efforts in developing sophisticated recommendation and personalization systems.

Key Responsibilities

Design, train, and deploy recommendation and personalization models using deep learning, sequence models (Transformers, GRU), and boosted trees (XGBoost, LightGBM).
Develop multi-objective ranking systems that integrate engagement, conversion, and merchant value into a single ranking score, utilizing multi-task learning.
Build scalable two-stage retrieval and ranking systems, including ANN retrieval over embeddings feeding learning-to-rank models.
Collaborate with infrastructure teams to productionize real-time feature pipelines.
Define serving-time impression and feature logging to mitigate training-serving skew and generate unbiased training data.
Design and execute online experiments with rigorous guardrail metrics, correcting for bias and applying off-policy evaluation to attribute lift accurately.
Integrate model outputs with platform APIs for dynamic personalization across search, home feeds, and store pages.
Define best practices for offline evaluation and online experimentation metrics.
Partner with product analytics and data science teams to iterate on signal enrichment and cold-start strategies.
Mentor junior data scientists and establish best practices within the team.

Required Qualifications and Experience

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field.
A minimum of 5-10 years of relevant experience.
At least 4 years of hands-on ML experience, including 2+ years in designing or deploying large-scale recommendation systems.
A track record of building or maintaining systems serving 1M+ users or generating 100M+ personalized predictions daily.
Deep expertise in representation learning, embeddings, attention mechanisms, and multi-task learning.
Demonstrated success in integrating multi-stage ranking systems across e-commerce surfaces with measurable online lift.
Proficiency with large-scale data ecosystems such as Kafka, Spark, ClickHouse, or BigQuery.
Strong command of experimentation rigor, including guardrail metrics, bias correction, and off-policy evaluation.
Skilled in debugging, optimization, and productionization of ML pipelines in cloud or containerized environments.