Lead Data Scientist

UMATR; Jeddah; On-site; SAR 200,000 - 300,000; Full time

Job summary

An e-commerce platform in Saudi Arabia is seeking a Lead Data Scientist specializing in integrity and safety. This role focuses on building AI-driven systems to detect fraud and maintain platform quality. The ideal candidate will have substantial experience in machine learning and team leadership, improving marketplace trust. Your insights will protect millions of users, and you'll have opportunities for professional growth with medical benefits and performance bonuses.

Benefits

Medical Health Insurance

Performance Bonus

Additional perks and growth opportunities

Qualifications

• 5+ years of applied ML experience, with 2+ years in Trust & Safety, Integrity, or Fraud Detection systems.
• Experience with multimodal text-image modeling and policy classification.
• Strong analytical reasoning and cross-functional collaboration skills.

Responsibilities

• Build and deploy supervised and unsupervised ML models for fraud detection.
• Lead the Integrity, Safety & Trust pod and mentor applied data scientists.
• Collaborate with teams to define integrity policies.

Skills

Python

SQL

Machine Learning

NLP

Data Visualization

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field

Tools

PyTorch

Transformers

Scikit-learn

OpenCV

Kafka

Redis Streams

Job description

Overview

Title: Lead Data Scientist – Integrity & Safety

Tech Stack: Python, SQL, PyTorch, Transformers, Scikit-learn, OpenCV, NLP, Multimodal (CLIP/ViT + BERT), Graph Learning, Kafka/Redis Streams

What You’ll Do

As the Senior Data Scientist for Integrity & Trust, you will protect millions of buyers and sellers by building AI-driven defense systems that detect fraud, remove counterfeit products, and maintain platform quality. Your work directly impacts trust and growth in a high-COD environment, ensuring the platform remains secure and reliable.

You will:

• Build and deploy supervised and unsupervised ML models for policy violation, counterfeit, and fraud detection.
• Lead and grow the Integrity, Safety & Trust pod, mentoring applied data scientists and delivering end-to-end projects with measurable business outcomes.
• Design feature pipelines leveraging product text, images, seller behavior, and transaction data.
• Apply NLP models for text classification, entity extraction, and multilingual moderation (Arabic + English).
• Develop graph-based and anomaly detection models to identify coordinated or suspicious merchant activity.
• Collaborate with product, legal, and operations teams to define integrity policies and feedback loops.
• Implement dashboards and real-time monitoring for detection and escalation (Elastic, Grafana).
• Optimize model precision/recall tradeoffs balancing enforcement and user experience.
• Work with graph learning, anomaly detection, and multimodal data pipelines.

Who They Are

You’ll be joining a high-growth e-commerce platform focused on marketplace trust and safety. The team operates in a complex, fast-paced environment where your AI solutions will directly impact millions of users. This is a chance to lead a critical function, scale a data science team, and implement cutting-edge AI techniques to ensure platform integrity.

What Is In It For You

• Medical Health Insurance
• Performance Bonus
• Additional perks and growth opportunities
• 35k SAR

Who You Are

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
• 5+ years of applied ML experience, with 2+ years in Trust & Safety, Integrity, or Fraud Detection systems
• Experience with multimodal text-image modeling (OCR, CLIP/ViT, layout analysis), taxonomy/attribute extraction, policy classification, and Arabic/English content moderation
• Strong Python, SQL, and ML library skills (PyTorch, Transformers, Scikit-learn, OpenCV)
• Experience developing streaming or near-real-time detection systems (Kafka, Redis Streams, or equivalent)
• Knowledge of e-commerce ecosystems, product policy enforcement, and counterfeit/low-quality detection is a plus
• Proven ability to build and grow applied data science teams and deliver measurable business outcomes
• Excellent analytical reasoning, communication, and cross-functional collaboration skills, with a strong ability to balance enforcement precision with business impact