• Support management for key business decisions by performing deep-dive analysis and translating results into actionable insights.
• Regularly follow up on main company KPIs and its drivers, analyze gaps against expectations, and propose potential improvements.
• Monitor market dynamics, analyze competitors’ moves, assess its impact on KPI performance, and propose relevant activities.
• Answer business-related questions through exploratory data analyses and ad-hoc reporting that helps drive engagement, retention, and monetization.
• Translate ad-hoc requests into reusable data tools that can scale to answer broader questions.
• Handle the game team’s data assets by defining key game events, architecting data models, and defining data quality governance.
• Build standard KPI dashboards/reports that signal game health, tracking all content/feature releases, readouts, and analysis, empowering feature owners to run performance for the business.
• Identify opportunities for experimentation and recommend appropriate methodology. Generate hypotheses for future product features.
• Collaborate closely with product teams on a daily basis on new feature development, and track its performance from the first day of the release.
• Design and interpret A/B tests and multivariate experiments.
• Collaborate with technical leads, analysts, data scientists, and game teams to drive key strategic initiatives for the improvement of the data and analytics infrastructure.
• Partner with Data Engineers to manage data quality and integrity to support high-quality deliverables

Requirements:

• 2+ years of experience in data analytics or another quantitative analytics field, preferably in the gaming industry
• University degree in computer science, engineering or mathematics/statistics, economics, or relevant working experience
• Knowledge about in-depth business analysis, recognizing and monitoring key KPI indicators, understanding analytical tools and consoles, and data structures as a whole
• Experience in understanding the strengths and weaknesses of different statistical modeling approaches and can effectively reason about when to apply different combinations and iterate
• Deep knowledge of data visualization principles and dash-boarding building experience in one of these: Google Analytics, DataStudio, Tableau, Looker, Power BI, and/or similar
• Basic project management knowledge, utilizing software such as Trello or JIRA, and experience in an agile environment and iterative development.
• Personal characteristics: Gamer in the heart, Argumentative influencer, Solution-oriented, Analytical view, and structured work method, Able to prioritize workload, High initiative profile, Capable to communicate effectively

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