About the role
Punt is a social sweepstakes platform that lets players enjoy a wide variety of casino-style games using virtual currencies, a model that allows it to operate legally in many U.S. states where traditional online gambling is restricted. The platform has grown steadily since launch, expanding its game catalog and building a strong referral program, and offers a tiered VIP program that rewards players as they progress through gameplay milestones. As the business scales, we're building out our Data team to power smarter, faster decisions across the platform.
About the Role We're looking for a BI Analyst to build and maintain the reporting and modeling infrastructure that powers commercial decision making across the business. This role blends traditional BI work, including dashboards, visualizations, and query performance, with more advanced analytical work, including machine learning models for bonus abuse detection and player value estimation. You'll be a key technical contributor, ensuring our data is not just accurate and accessible, but genuinely predictive and actionable.
Key Responsibilities Dashboards & Visualization: Design, build, and maintain dashboards and reports that give stakeholders across CRM, Marketing, Product, and Commercial teams clear visibility into performance and player behavior. Query & Pipeline Efficiency: Write, optimize, and refactor SQL queries (Snowflake or similar) for performance and scalability; identify and resolve bottlenecks in existing pipelines and reporting models. Bonus Abuse Modeling: Build and maintain models to detect bonus/promo abuse patterns (e.g., multi-accounting, arbitrage, matched betting behaviors), working with CRM and Risk/Fraud teams to reduce cost leakage. Player Value Modeling: Develop and iterate on player value/LTV models, incorporating behavioral, transactional, and engagement data to support segmentation and VIP strategy. Machine Learning: Apply ML techniques (classification, clustering, regression) to problems such as churn prediction, propensity modeling, and player scoring; validate models against real world outcomes and monitor for drift. Data Quality & Governance: Ensure consistency, accuracy, and documentation of key metrics and data models used across BI outputs. Cross-Functional Support: Partner with CRM, Marketing, Product, and Commercial teams to understand reporting needs and translate them into scalable BI solutions. Ad Hoc Analysis: Respond to data requests and deep dive questions from stakeholders with rigor and speed.
Requirements 2 to 4+ years of experience in a BI, data analyst, or analytics engineering role, ideally within online gaming, casino, betting, or another high volume transactional consumer industry. Strong SQL skills, including experience optimizing queries for performance on large datasets (Snowflake preferred). Experience building dashboards/visualizations in BI tools (Looker, Tableau, Power BI, or similar). Practical experience with machine learning techniques (e.g., logistic regression, random forest, clustering) and comfort validating and explaining model outputs to non technical stakeholders. Proficiency in Python (pandas, scikit learn, or similar) for modeling and automation. Experience with or strong interest in fraud/abuse detection and player value/LTV modeling. Solid understanding of relational database structures and data modeling principles. Detail oriented, with an ability to balance technical depth with clear communication.
Nice to Have Experience with anomaly detection or unsupervised learning applied to fraud/abuse use cases. Familiarity with RFM or similar player segmentation frameworks. Exposure to A/B testing or experimentation design. Experience with orchestration tools (Airflow, dbt) for pipeline automation.
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About the role
Punt is a social sweepstakes platform that lets players enjoy a wide variety of casino-style games using virtual currencies, a model that allows it to operate legally in many U.S. states where traditional online gambling is restricted. The platform has grown steadily since launch, expanding its game catalog and building a strong referral program, and offers a tiered VIP program that rewards players as they progress through gameplay milestones. As the business scales, we're building out our Data team to power smarter, faster decisions across the platform.
About the Role We're looking for a BI Analyst to build and maintain the reporting and modeling infrastructure that powers commercial decision making across the business. This role blends traditional BI work, including dashboards, visualizations, and query performance, with more advanced analytical work, including machine learning models for bonus abuse detection and player value estimation. You'll be a key technical contributor, ensuring our data is not just accurate and accessible, but genuinely predictive and actionable.
Key Responsibilities Dashboards & Visualization: Design, build, and maintain dashboards and reports that give stakeholders across CRM, Marketing, Product, and Commercial teams clear visibility into performance and player behavior. Query & Pipeline Efficiency: Write, optimize, and refactor SQL queries (Snowflake or similar) for performance and scalability; identify and resolve bottlenecks in existing pipelines and reporting models. Bonus Abuse Modeling: Build and maintain models to detect bonus/promo abuse patterns (e.g., multi-accounting, arbitrage, matched betting behaviors), working with CRM and Risk/Fraud teams to reduce cost leakage. Player Value Modeling: Develop and iterate on player value/LTV models, incorporating behavioral, transactional, and engagement data to support segmentation and VIP strategy. Machine Learning: Apply ML techniques (classification, clustering, regression) to problems such as churn prediction, propensity modeling, and player scoring; validate models against real world outcomes and monitor for drift. Data Quality & Governance: Ensure consistency, accuracy, and documentation of key metrics and data models used across BI outputs. Cross-Functional Support: Partner with CRM, Marketing, Product, and Commercial teams to understand reporting needs and translate them into scalable BI solutions. Ad Hoc Analysis: Respond to data requests and deep dive questions from stakeholders with rigor and speed.
Requirements 2 to 4+ years of experience in a BI, data analyst, or analytics engineering role, ideally within online gaming, casino, betting, or another high volume transactional consumer industry. Strong SQL skills, including experience optimizing queries for performance on large datasets (Snowflake preferred). Experience building dashboards/visualizations in BI tools (Looker, Tableau, Power BI, or similar). Practical experience with machine learning techniques (e.g., logistic regression, random forest, clustering) and comfort validating and explaining model outputs to non technical stakeholders. Proficiency in Python (pandas, scikit learn, or similar) for modeling and automation. Experience with or strong interest in fraud/abuse detection and player value/LTV modeling. Solid understanding of relational database structures and data modeling principles. Detail oriented, with an ability to balance technical depth with clear communication.
Nice to Have Experience with anomaly detection or unsupervised learning applied to fraud/abuse use cases. Familiarity with RFM or similar player segmentation frameworks. Exposure to A/B testing or experimentation design. Experience with orchestration tools (Airflow, dbt) for pipeline automation.