Senior Data Scientist – Anti-Cheat / Anti-Fraud (Deep Learning)

Location: Global Remote

Company: A5 Labs

Why Join A5 Labs

At A5 Labs, we value strong technical talent and believe in rewarding long-term contribution.

What we offer

• Highly competitive base salary

• Quarterly performance bonus

• Annual salary increase based on performance

• 4–5 weeks of paid annual leave

• Work in a highly technical environment with strong focus on ML/DL and algorithms

• Opportunity to solve real-world anti-fraud and anti-cheat problems at scale

About the Role

A5 Labs is looking for a Senior Data Scientist to join our Anti-Cheat / Anti-Fraud team.

In this role, you will design and develop advanced machine learning and deep learning models to detect suspicious behaviors, fraudulent activity, and adversarial patterns in large-scale datasets.

We are looking for candidates with strong algorithmic capabilities and hands-on experience applying deep learning to fraud detection, abuse detection, or security-related problems.

Key Responsibilities

• Design and build machine learning / deep learning models for fraud and cheating detection
• Analyze large-scale behavioral and transactional datasets to identify abnormal patterns
• Develop scalable detection systems for fraud, abuse, or adversarial behaviors
• Apply advanced modeling approaches including deep learning architectures (e.g., Transformer-based models)
• Improve model performance through feature engineering, model optimization, and continuous evaluation
• Collaborate with engineering teams to deploy and maintain production-ready models
• Translate complex risk and security problems into practical data science solutions

Requirements

• 5+ years of experience in Data Science, Machine Learning, or related fields
• Strong hands-on experience with Deep Learning
• Experience in anti-fraud, anti-cheat, abuse detection, risk modeling, or security-related ML
• Strong algorithmic and modeling skills
• Proficiency in Python and common ML/DL frameworks
• Experience working with large-scale datasets and production models
• Ability to work independently in a highly technical environment

Preferred Qualifications

• Experience with Transformer-based models or advanced deep learning architectures
• Background in Trust & Safety, Fraud Detection, or Security Analytics
• Experience with anomaly detection or behavioral modeling systems