Senior Data Scientist - Anticheating

About the Role We are building a next-generation AI-driven anti-cheating system for competitive strategy games. Unlike traditional fraud detection, our challenge sits at the intersection of: 🎮 Game AI & player behavior modeling 🧠 Reinforcement learning & decision systems 🔍 Anomaly detection under adversarial conditions You will work on identifying non-obvious, strategic cheating behaviors in complex environments where players actively adapt to detection systems. This is not rule-based detection — this is behavioral intelligence at scale. What You’ll Do 1️⃣ Behavioral Modeling & Detection Design machine learning / deep learning models to detect cheating patterns Model player behavior sequences, strategies, and anomalies Build systems that distinguish: high-skill play vs. AI-assisted play natural variance vs. exploitation 2️⃣ Anti-Cheating System Design Develop scalable detection pipelines (offline + real-time) Build feature systems from gameplay logs / event streams Design evaluation frameworks for detection accuracy & robustness 3️⃣ ML / DL / Advanced Techniques Apply and experiment with: sequence modeling (RNN / Transformer-based) anomaly detection graph-based or behavioral embeddings Explore intersections with: reinforcement learning game-theoretic modeling adversarial ML 4️⃣ Collaboration with AI & Engineering Teams Work closely with: Gameplay AI / RL researchers Backend / data engineering teams Translate models into production systems What We’re Looking For ✅ Core Requirements 4+ years in Data Science / Machine Learning roles Strong foundation in: deep learning statistical modeling Experience in one or more of: fraud detection / AML risk modeling anomaly detection behavioral analytics ✅ Strong Signals (Big Plus) Experience with: sequence models (LSTM / Transformer) large-scale behavioral data real-time detection systems Exposure to: reinforcement learning game AI adversarial systems ✅ Technical Stack Python (must) PyTorch / TensorFlow SQL / data pipelines Experience working with large-scale datasets Why This Role is Interesting 🚀 Work on problems similar to fraud detection at scale — but harder 🎯 Direct impact on real-money / competitive environments 🧠 Blend of: ML research production systems game AI 🌍 Fully remote, globally distributed team Location & Visa 🌏 Remote-first (global team) 🇯🇵 Japan relocation supported (visa sponsorship available for qualified candidates) Who This Role is Perfect For Data scientists bored with “dashboard ML” Fraud / AML experts who want more complex, adversarial systems ML engineers who want to work closer to decision intelligence & behavior modeling Originally posted on Himalayas