**About Us:**Betty is an innovative entertainment company pioneering at the intersection of real-money online casinos and casual mobile gaming.
Betty Canada is a scale up company accredited by the Alcohol and Gaming Commission of Ontario (AGCO) as a B2C operator in February 2023, we’ve set a new standard in the industry.
Our mission is to redefine the online casino experience by offering a uniquely transparent environment where players can relax, unwind, and enjoy themselves safely. We are committed to accessibility, fairness, and inclusivity, fostering a community of like-minded individuals who value ethical gaming practices and prioritize our players’ safety and enjoyment above everything else.
Our Values:
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We are honest – we value honesty in all aspects.
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Bring the Olives – we offer premium customer experience.
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Think Big – we believe in always striving for more.
Key Responsibilities
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Design, build, test, and deploy predictive and prescriptive models (e.g., churn prediction, player lifetime value, segmentation, risk classification, fraud detection).
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Analyze large-scale player behavioral data to identify key value drivers and recommend optimizations for promotions, engagement, and monetization strategies.
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Develop models for anomaly detection, fraud prevention, and responsible gaming interventions to maintain a safe and compliant environment.
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Design and evaluate A/B and multivariate tests for product features and marketing campaigns, ensuring statistically robust insights.
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Partner with Data Engineers to ensure model pipelines are production-ready, automated, and scalable across cloud environments.
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Visualize and present analytical findings to both technical and non-technical stakeholders, driving clear, data-informed decisions.
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Monitor and refine model performance, automate recurring analyses, and ensure data quality and reproducibility.
Requirements
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3+ years of experience in a Data Scientist, Machine Learning Engineer, or advanced analytics role (ideally within iGaming, FinTech, or other consumer-facing digital products).
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Strong theoretical understanding of machine learning and statistical algorithms (classification, regression, clustering, optimization).
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Proven experience applying models to solve business problems (e.g., forecasting, segmentation, retention, player value optimization).
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Skilled in Python (Pandas, NumPy, Scikit-learn, PySpark) and SQL (advanced querying, ETL processes, performance optimization).
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Experienced in analyzing massive datasets (100M+ rows) across multiple sources.
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Strong communication skills — able to explain complex technical concepts to non-technical audiences.
Nice to Have
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Experience with AWS, Docker, Kubernetes, or other cloud and containerization technologies.
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Background in NLP, time-series, or causal inference modeling.
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Proficiency with data visualization tools (Tableau, Looker, or Power BI).
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Experience integrating data and models into production pipelines and dashboards.
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Familiarity with iGaming KPIs such as LTV, ARPDAU, Churn, and Player Retention metrics.
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Understanding of A/B testing frameworks and experimental design.