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).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 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 InsurancePerformance BonusAdditional perks and growth opportunities35k SARWho You Are:
Bachelor's or Master's degree in Computer Science, Data Science, or a related field5+ years of applied ML experience, with 2+ years in Trust & Safety, Integrity, or Fraud Detection systemsExperience with multimodal text-image modeling (OCR, CLIP/ViT, layout analysis), taxonomy/attribute extraction, policy classification, and Arabic/English content moderationStrong 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 plusProven ability to build and grow applied data science teams and deliver measurable business outcomesExcellent analytical reasoning, communication, and cross-functional collaboration skills, with a strong ability to balance enforcement precision with business impact
