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Senior Data Scientist - Recommendation Systems Pod

3 weeks ago
Saudi Arabia
Full-time
Senior
Data Scientist
Data Science and Analytics
Apache Spark ClickHouse Deep Learning GCP Kafka LightGBM Transformers XGBoost
Apply Now
Salla E-Commerce Platform

Salla E-Commerce Platform

Salla E-Commerce Platform (salla.sa) offers smart and easy e-commerce solutions for merchants, enabling direct selling to customers with ease.

Internet Software & Services
251-1K
Founded 2016
$8M raised
View All Jobs 3

Description

  • Design, train, and deploy recommendation and personalization models using deep learning, sequence models, and boosted trees.
  • Develop multi-objective ranking models that balance engagement, conversion, and merchant value.
  • Build scalable two-stage retrieval and ranking systems using ANN retrieval and learning-to-rank objectives.
  • Collaborate with infrastructure teams to productionize real-time feature pipelines.
  • Define serving-time impression and feature logging to reduce training-serving skew and improve training data quality.
  • Design and run online experiments with guardrail metrics, bias correction, and counterfactual evaluation methods.
  • Integrate model outputs with platform APIs for dynamic personalization across search, home feeds, and store pages.
  • Establish best practices for offline evaluation and online experimentation metrics.
  • Partner with product analytics and data science teams on signal enrichment and cold-start strategies.
  • Mentor junior data scientists and help define team best practices.

Requirements

  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field.
  • 4+ years of hands-on machine learning experience, including 2+ years designing or deploying large-scale recommendation systems.
  • Experience 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 integrating multi-stage ranking systems across e-commerce surfaces with measurable online lift.
  • Proficiency with large-scale data ecosystems such as Kafka, Spark, ClickHouse, BigQuery, or equivalent.
  • Strong command of experimentation rigor, including guardrail metrics, position-bias correction, off-policy/counterfactual evaluation, and model monitoring.
  • Experience debugging, optimizing, and productionizing ML pipelines in cloud or containerized environments.

Interested in this position?

Apply directly on the company website

Apply Now

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