Game Security Data Scientist
$154,000–$211,000 year
On-siteEl Segundo, California, United States
El Segundo, California, United StatesOn-siteFull Time$154,000–$211,000 yearSenior LevelDoctorate Or Professional DegreeLarge
Full TimeSenior LevelDoctorate Or Professional DegreeLarge
Job Summary
Develop and improve ML models to detect abnormal user behavior and cheating in games by analyzing large-scale game logs, user behavior data, and security events. Identify detection features, design detection logic, and visualize metrics to enhance KSS operational efficiency. Collaborate with game studios, security engineers, and stakeholders to support security operations and enforcement responses. Evaluate model performance, analyze false positives and false negatives, and drive improvements based on data.
Required Qualifications
- Degree in a related field such as Machine Learning, Deep Learning, Statistics, or Computer Science, or equivalent practical experience
- Experience with ML-based modeling projects such as anomaly detection, classification, prediction, or pattern analysis
- Ability to analyze large-scale log and event data using Python, SQL, or similar tools
- Understanding of the end-to-end data workflow, including log data cleansing, feature engineering, training data construction, and model evaluation
- Experience understanding the structure of machine learning/deep learning models and improving models according to their objectives
- Ability to perform feature engineering with consideration for data quality, reproducibility, and scalability
- Ability to quantitatively evaluate model performance and identify improvement directions from the perspective of false positives and false negatives
- Ability to define problems independently and drive improvements based on data
Desired Qualifications
- Experience using game data for Anti-Cheat, cheating/abuse detection, or abnormal behavior analysis
- Gameplay experience in various game genres such as FPS/TPS, battle royale, or MMORPG, or understanding of the data characteristics of these genres
- Experience detecting abnormal patterns based on user behavior data and improving models or detection logic
- Experience processing large-scale log data and building or operating ML pipelines
- Experience using, or understanding of, large-scale data platforms such as Spark and Hadoop
- Experience collaborating with global organizations/studios, or communication skills in Korean or a second language
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