Game Security Data Scientist

KRAFTON

$154K — $211K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Degree in Machine Learning, Deep Learning, Statistics, Computer Science, or equivalent experience
  • Experience with ML-based projects like anomaly detection or classification
  • Proficient in analyzing game logs using Python, SQL, or similar tools
  • Strong understanding of end-to-end data workflows for model development
  • Experience in improving machine learning models for specific objectives
  • Skilled in feature engineering with focus on data quality and scalability
  • Ability to evaluate model performance and identify enhancements focusing on false positives and negatives

Responsibilities

  • Develop and enhance ML models to detect user behavior anomalies
  • Analyze large-scale game logs and user behavior data for detection purposes
  • Identify cheating patterns and improve detection logic
  • Support data analysis in security operations and enforcement
  • Design and visualize metrics to enhance detection efficiency
  • Collaborate with game studios and security engineers
  • Evaluate and refine detection models, addressing false positives and negatives

Benefits

  • Access to a diverse and inclusive workplace culture
  • Opportunities for professional development and training
  • Collaboration with global teams and game studios
  • Engagement with cutting-edge gaming security technologies
  • Flexibility with work arrangements to promote work-life balance
Full Job 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

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

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


In California, the expected salary range for this position is $154,000-$211,000. The listed expected salary range represents a good faith estimate and the actual pay may depend on a variety of job-related factors that can include experience, education, skills, and location.

Don't meet every single requirement?


Studies have shown that women and people of color are less likely to apply at jobs unless they meet every single qualification. At Krafton we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You might just be the right candidate for this or other roles.

Due to recent scams, our recruiters will only reach out to you via [redacted].com, [redacted].com or [redacted].com. If you received an email and are unsure you can always email [redacted].

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