Data Scientist
Role details
Job location
Tech stack
Job description
- Lead the data science work across the model lifecycle, from exploratory analysis and feature development through evaluation, monitoring, and partnership with engineering on deployment.
- Design and develop statistical and machine learning models to detect cheating, botting, account boosting, mass account creation, account abuse, payment fraud, and other suspicious gameplay or platform behaviors.
- Build and improve features, risk signals, and detection approaches using gameplay telemetry, player behavior, account lifecycle, registration, transaction, and game event data.
- Continuously evaluate and improve detection effectiveness by measuring model performance, reducing false positives, and adapting to evolving abuse patterns.
- Collaborate with game teams, security engineers, product partners, fraud stakeholders, and anti-cheat teams to support data-informed detection and enforcement strategies.
- Communicate analytical findings clearly to technical and non-technical stakeholders, including model performance, limitations, tradeoffs, confidence levels, and recommended actions.
Requirements
This role is ideal for a data scientist who is analytical, curious, collaborative, and comfortable working with complex data in an adversarial environment where player behavior and abuse patterns evolve over time., * 5+ years of experience in data science, machine learning, applied statistics, risk modeling, security analytics, fraud detection, or a related analytical field.
- Strong experience with Python or R and advanced SQL.
- Experience building statistical or machine learning models using large-scale behavioral, event, transaction, account, or telemetry data.
- Strong understanding of model evaluation, including precision and recall tradeoffs, false positive analysis, thresholding, noisy labels, and delayed outcomes.
- Ability to work cross-functionally with engineering, product, operations, security, or game teams and explain complex analytical findings clearly., * Experience in gaming, gameplay security, anti-cheat, fraud detection, trust & safety, cybersecurity, bot detection, or another adversarial domain.
- Experience with one or more of the following areas: cheating, botting, account boosting, mass account registration, fake account detection, account abuse, payment fraud, chargebacks, or abnormal gameplay behavior.
- Experience developing features from behavioral, transactional, registration, account lifecycle, or gameplay telemetry data.
- Experience partnering with engineering teams to operationalize models, detection signals, dashboards, monitoring workflows, or data pipelines.
- Familiarity with cloud, data, or ML platforms such as AWS, Google Cloud Platform, Spark, Databricks, Snowflake, Hive, Kafka, Airflow, Kubernetes, or similar technologies.
Benefits & conditions
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.