Game Security Data Scientist

Duties

• Enhance the data analytics and ML-based detection capabilities provided by KSS, and develop models that can quickly and accurately detect and classify abnormal behavior and cheating in games.
• Analyze large-scale game logs and user behavior data, improve the performance of detection models, and support the effective use of detection results in security operations and enforcement response.
• Develop and improve ML models to detect abnormal user behavior and cheating in games.
• Develop and enhance detection logic based on identified cheating patterns and detection features.
• Support data analysis for security operations and enforcement response.
• Design and visualize metrics to improve KSS detection and operational efficiency.
• Evaluate detection model performance, analyze false positives and false negatives, and improve model quality.

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.
• Understanding of the end-to-end data workflow, including log data cleansing, feature engineering, training data construction, and model evaluation.
• 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.

Preferred 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.