Data Scientist

Within the Editorial & Content Intelligence department, the Data Scientist brings advanced data science expertise to several dimensions of video games analytics. The role focuses on building predictive models, conducting deep statistical analyses, and generating high-impact business insights that support strategic decision making across Bandai Namco Entertainment Europe’s portfolio.

Your main responsibilities will include (non-exhaustive list):

Lead Data Science & Advanced Analytics Initiatives

• Design, develop, and deploy predictive models using Python and machine learning frameworks
• Conduct advanced statistical analyses: hypothesis testing, regression modeling, time series analysis, causal inference, and cohort-based studies
• Build player segmentation models using clustering and behavioral analysis

Manage In-Game Behavioral Analytics

• Support the appropriate events definition and tag plan
• Analyze player behavioral data to generate post-launch and live-ops insights
• Support A/B testing design and interpretation for in-game features and content updates
• Work alongside the team to ensure data quality and analytical consistency on in-game datasets housed in Snowflake

Develop NLP-Powered Player Feedback Intelligence

• Design and build NLP pipelines to collect, process, and analyze player feedback at scale from multiple sources
• Develop sentiment analysis models to track player satisfaction trends
• Leverage LLMs and GenAI for feedback summarization and classification

Shape the Analytics Strategy & Platform Usage

• Contribute to the analytics roadmap by identifying where advanced modeling and automation can improve existing processes
• Leverage Snowflake and Microsoft Fabric as core platforms for data analysis, model development, and insight delivery
• Promote best practices in statistical rigor, reproducibility, and documentation

Create Impactful Reporting & Data Visualizations

• Develop automated dashboards and reports using Power BI and Microsoft Fabric
• Enable stakeholder autonomy through well-documented, self-service dashboards and data literacy support