A5 Labs
Senior Data Scientist - Anticheating
Remote in set countriesJapan onlyFull-time
Posted 22 AprConfirmed open 1h ago
Who can apply
Japan only
Salary
Not disclosed
Level
Senior
Full-time
Timezone
Not stated
About the role
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
Skills mentioned
Interested in this role?
You apply directly with A5 Labs. Remotavia never charges candidates.
Check your resume
See which keywords from this job your resume is missing.
Track this application
Add it to your board and get a follow-up reminder.
Draft a cover letter
An honest first draft from your resume and this job.
Prepare for interviews
Likely questions based on this job description.
About A5 Labs
Listing details & historyShowHide
- Employer posted
- 22 Apr 2026
- Last confirmed open
- 1h ago
- Source
- Employer careers site
- Degree
- Not mentioned
- Visa
- Sponsorship offered
- “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”
- Timezone
- Not stated
- Languages
- Not stated
- Location evidence
- “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”
Details are read from the listing text. They are not a guarantee of work authorization; confirm with the employer.
