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Potential Responsibilities 1. Fraud Detection & Prevention Develop and maintain ML models to detect and prevent in-game fraud, including monitoring the in-game economy, identifying emerging patterns, and generating regular reports. Conduct deep dives on confirmed fraud cases to extract behavioral signatures, propose predictive variables, and improve model accuracy. Collaborate with an anti-fraud task force to refine dashboards, share insights, and ensure swift response to new fraud patterns. 2. Matchmaking & Skill Rating Design and implement robust metrics to evaluate matchmaking quality across different game modes. Enhance and research next-generation ML-based skill rating and matchmaking solutions to optimize the online player experience. Monitor matchmaking performance, proactively identify issues, and communicate findings to stakeholders. 3. Recommender Systems & Personalization Research and develop recommendation frameworks for in-game ads and promotions based on player behavior and preferences. Track experiment performance, analyze results, and recommend adjustments or improvements. Collaborate with stakeholders to refine targeting strategies and maximize player engagement. 4. Data Analysis & Reporting Create and maintain dashboards to visualize key metrics, monitor model performance, and communicate insights. Produce periodic reports to inform decision-making and guide product improvements. Ensure data quality and reliability throughout all analytics and model deployment processes.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal. com.

To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: . Gaming Background 1. Educational & Technical Background Advanced degree in Computer Science, Data Science, Statistics, or related field. Strong programming skills in Python, proficiency with machine learning libraries, and solid SQL expertise. Familiarity with deep learning frameworks (e. g., PyTorch, TensorFlow) and experience in anomaly detection or semi-supervised learning. 2. Machine Learning & Modeling Proven experience in model development, diagnostics, maintenance, and deployment. Understanding of A/B testing, reinforcement learning, multi-armed bandits, and experimental design. Ability to handle large-scale user behavior data and extract actionable insights. 3. Analytical & Communication Skills Strong data analysis and pattern recognition capabilities, with a knack for translating findings into clear, concise reporting. Effective communicator able to collaborate with cross-functional teams and influence decision-making. Detail-oriented and reliable, delivering high-quality work with minimal supervision. 4. Domain Knowledge & Tools Experience with data visualization, dashboarding, and analytics reporting. Knowledge of cloud-based platforms and tools (e. g., AWS, Snowflake, Databricks, Sagemaker). Familiarity with gaming industry concepts, particularly basketball mechanics and game dynamics, is a plus. 5. Soft Skills: o Strong communication and proactive personality - not an order taker o Willingness to understand the product in depth - must play the games to understand the issues o Contribute to the team with new ideas while taking ownership of their work.