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