Lead Data Scientist - Integrity & Safety

Protect millions of buyers and sellers as our Senior Data Scientist for Integrity & Trust. You\'ll lead building the AI defense systems that detect fraud, eliminate counterfeit products, and maintain marketplace quality across our platform. In MENA\'s high-COD environment (75% of transactions), trust is everything. Your models will be the difference between platform growth and reputation damage.

Responsibilities

Build and deploy supervised and unsupervised ML models for policy violation detection, counterfeit detection, and fraud detection.

Build and grow the Integrity, Safety & Trust pod, mentor applied data scientists and deliver end-to-end projects with measurable business outcomes.

Design feature pipelines that leverage product text, images, seller behavior, and transaction data.

Apply NLP models for text classification, entity extraction, and multi-lingual moderation (Arabic + English).

Utilize multimodal architectures (CLIP, ViT + BERT) for image–text cross-validation.

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 monitoring for real-time detection and escalation (e.g., Elastic, Grafana).

Optimize model precision / recall tradeoffs based on enforcement and user experience goals.

Familiarity with graph learning, anomaly detection, and multimodal data pipelines.

Qualifications

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

5+ years of experience in applied ML, with at least 2+ years focused on Trust & Safety, Integrity, or Fraud Detection systems.

Experience with multi-modal text-image modeling (e.g., OCR, CLIP / ViT, layout analysis), taxonomy or attribute extraction, policy classification, and Arabic / English content moderation.

Strong proficiency in Python, SQL, and ML libraries such as PyTorch, Transformers, Scikit-learn, and 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 or low-quality detection is a plus.

Proven experience building or growing a team of applied data scientists and delivering end-to-end projects with measurable business outcomes.

Excellent analytical reasoning, communication, and cross-functional collaboration skills; able to balance enforcement precision with business impact.

Benefits

Medical Health Insurance

Performance Bonus

Others

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