Game Security Data Scientist
Indexed description
THE OPPORTUNITY
We develop, apply, and operate game security solutions and security operations systems to create a trusted gameplay environment for KRAFTON games.
Centered around KRAFTON Security Services (KSS), we provide core capabilities and services required for game security, including Anti-Cheat, Anti-Tamper, security operations, data analysis, and ML-based detection.
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.
You will 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.
Responsibilities
- Develop and improve ML models to detect abnormal user behavior and cheating in games
- Detect anomalies by analyzing large-scale game logs, user behavior data, and security events
- Analyze cheating patterns, identify detection features, and design and enhance detection logic
- Support data analysis for security operations and enforcement response
- Design and visualize metrics to improve KSS detection and operational efficiency
- Collaborate with game studios, security engineers, and other stakeholders
- Evaluate detection model performance, analyze false positives and false negatives, and improve model quality
- Degree in a related field such as Machine Learning, Deep Learning, Statistics, or Computer Science, or equivalent practical experience
- 5+ years of experience with ML-based modeling projects such as anomaly detection, classification, prediction, or pattern analysis within a gameplay environment
- 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
- 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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