Business Intelligence Analyst

About Punt

Punt offers a social sweepstakes platform enabling users to engage with diverse casino-style games using virtual currency, allowing operations in several U.S. states where conventional online gambling is restricted. Since launching, Punt has steadily expanded its gaming selection and referral initiatives, alongside a tiered VIP program rewarding players as they achieve gameplay milestones. As the business grows, the Data team is expanding to drive quicker and more insightful decision-making.

Role Overview

The Business Intelligence Analyst will be responsible for developing and sustaining the reporting and data modeling framework that supports strategic choices across the company. This position combines traditional BI tasks—like producing dashboards and optimizing reports—with advanced analytical work such as creating machine learning models to detect bonus abuse and estimate player value. The role demands expertise in ensuring data accuracy, accessibility, and relevance for predictive business impact.

Responsibilities

• Design, develop, and maintain comprehensive dashboards and visualizations to provide stakeholders in CRM, Marketing, Product, and Commercial units with transparent insights into performance and user engagement.
• Craft, refine, and optimize complex SQL queries in environments like Snowflake, improving query speed and pipeline scalability while addressing system bottlenecks.
• Develop and support models to identify patterns of bonus and promotional abuse, collaborating closely with CRM and risk management teams to mitigate revenue losses.
• Create and refine player value and lifetime value (LTV) models by analyzing behavioral, transactional, and engagement data to enhance customer segmentation and VIP program strategies.
• Implement machine learning methods (classification, clustering, regression) for functions such as churn prediction and player scoring, validating outcomes and monitoring model performance over time.
• Guarantee data consistency, accuracy, and comprehensive documentation for key metrics and data models utilized in BI deliverables.
• Collaborate with cross-functional teams to gather reporting needs and translate them into effective, scalable BI solutions.
• Conduct detailed and efficient on-demand data analyses and address inquiries from stakeholders promptly and thoroughly.

Qualifications

• 2 to 4+ years in BI, data analysis, or analytics engineering, preferably within online gaming, casino, betting, or other high-volume transactional consumer sectors.
• Strong command of SQL with proven experience optimizing queries for large-scale datasets, ideally within Snowflake environments.
• Hands-on experience designing dashboards and visualizations using tools like Looker, Tableau, Power BI, or similar platforms.
• Applied knowledge of machine learning techniques such as logistic regression, random forest, and clustering, and ability to communicate model insights clearly to non-technical audiences.
• Proficiency in Python, especially libraries like pandas and scikit-learn, for data modeling and automation purposes.
• Interest or experience in fraud or abuse detection and player value or LTV modeling.
• Strong understanding of relational database concepts and data modeling best practices.
• Attention to detail with excellent capability to balance deep technical analysis and clear communication.

Preferred Skills

• Experience applying anomaly detection or unsupervised learning methods to fraud and abuse use cases.
• Knowledge of player segmentation frameworks like RFM.
• Familiarity with experimentation design and A/B testing methodologies.
• Experience with workflow orchestration tools such as Airflow or dbt for automating data pipelines.