ML-Driven Game Security Data Scientist

Krafton; El Segundo (CA); On-site; USD 154,000 - 211,000; Full time

Job summary

KRAFTON is seeking a data science professional to enhance ML-driven detection for KSS, analyzing large-scale game logs and user behavior data to identify and classify anomalies and cheating across games. The role emphasizes building robust detection features, evaluating model performance, and collaborating with global studios to strengthen security operations.

The candidate should have a degree in ML/CS or equivalent, hands-on experience with Python/SQL, and a strong focus on data 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
• 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

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

Job description

KRAFTON is seeking a data science professional to enhance ML-driven detection for KSS, analyzing large-scale game logs and user behavior data to identify and classify anomalies and cheating across games. The role emphasizes building robust detection features, evaluating model performance, and collaborating with global studios to strengthen security operations.

The candidate should have a degree in ML/CS or equivalent, hands-on experience with Python/SQL, and a strong focus on data quality,