Senior Data Analyst - Poker

Job description

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: Zynga Poker is seeking a Senior Data Analyst to help drive decisions that impact millions of players worldwide. As part of our analytics team, you'll play a crucial role in shaping the future of our game through data-driven insights. Here's how you'll shape the player experience: Product Strategy: Analyze long and short-term trends to deliver insights that influence product direction Experimentation: Design statistically sound experiments that drive measurable impact Business Intelligence: Maintain comprehensive dashboards and ETL pipelines to keep the organization informed on game performance Game Integrity: Enhance fraud detection and bad actor models to maintain a healthy gaming ecosystem Join us if you love solving analytical puzzles that impact millions! What You'll Do: Collaborate with the Product team to enhance revenue, retention, and engagement metrics. This includes conducting A/B testing, performing insights analysis, and developing dashboards. Analyze player behaviour to understand motivations and preferences, partnering with game design and consumer insights teams to translate findings into actionable experience improvements. Design and maintain ETL pipelines to extract, transform, and load data from multiple sources, ensuring source of truth for analyses and business intelligence. Design game telemetry to capture meaningful player interaction data to improve the game experience. Design and maintain a suite of highly visible dashboards used by game leadership and game designers to make strategic decisions for Zynga Poker Support the economy team in tuning the different features in the game to optimize for long term game and feature health Play a leading role in the design and continuous improvement of our fraud and bad actor models Actively play and engage with our games to maintain first-hand understanding of player experience, game mechanics, and potential pain points. Monitor and maintain the integrity of a wide range of tools and models used to streamline workflows and personalize the player experience, in collaboration with other data analysts and scientists on the team. Participate in and contribute to the Analytics Org’s AI initiative, which aims to significantly increase each analyst’s impact through the power of LLMs Continuously learn about analytics best practices, and actively share and promote these practices across various games and teams. What You Bring: Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field. Advanced degrees (Masters or PhD) are a plus. Minimum of 4 years in data science or analytics roles, preferably in a Product Data Science or Gaming Analytics team Demonstrated experience guiding product teams through complex decisions and analyses and dealing with ambiguous data Proficiency in Python and SQL. Demonstrated experience in data