The Senior Data Analyst, Product Analytics at Mistplay will enhance business performance through insightful analysis and a dynamic analytics strategy. The role involves proactive analysis of product funnels, user cohorts, and behaviors to identify growth opportunities. Responsibilities include defining KPIs, building automated dashboards, reports, and models, and designing, running, and analyzing A/B and multivariate experiments to improve features and test new ideas. This position collaborates closely with Product and Lifecycle teams on user-focused initiatives and reports to the Manager of Data Analytics and Experimentation.
Conduct proactive analyses of product funnels, user cohorts, and user behaviors to identify growth opportunities.,Define Key Performance Indicators (KPIs) and build automated dashboards, reports, and models to inform team decisions.,Design, execute, and analyze A/B and multivariate experiments to enhance product features and test new concepts.,Collaborate with Product and Lifecycle Managers on planning and analyzing A/B tests and engagement campaigns.,Drive insights reporting to guide the release of new product features and engagement strategies.,Synthesize and clearly communicate complex concepts and analyses to diverse technical and non-technical audiences.
Bachelor's Degree (BA/BS) in Computer Science, Mathematics, Economics, Statistics, or another quantitative field.,3-4 years of experience in quantitative analysis, preferably within the tech industry.,Demonstrated ability to impact business or product decisions.,Strong foundational knowledge of inferential statistics concepts (e.g., significance, power, confidence intervals, variance).,Prior experience with A/B testing.,Familiarity with online lifecycle marketing concepts, including email, push notifications, and attribution strategies.
Bachelor's Degree
Mistplay is a pioneering mobile loyalty platform that rewards users for playing and discovering new mobile games. It empowers game studios to acquire and deeply engage users globally by leveraging in-game data and machine learning to recommend relevant games, fostering user loyalty and driving retention and in-app purchase spending. [cite:2, 1.1, 1.2, 1.3, 1.4, 2.2, 3.2]
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