openteamtailoralven
Lead Data Analyst
Madbox
LocationMadbox Barcelona, Madbox Paris
Workplacehybrid
Posted2026-06-11T11:11:55+02:00
Last observed2026-06-23 23:25:31.961050
Job idalven-madbox:teamtailor:9c3eceff-e88d-4d80-ae57-6d5c68e4de7a
Madbox is a fast-growing mobile gaming company with a very unique way of developing games. Everything has been made for teams to take as much ownership as possible, unleash their creativity , bring performance , and have as much fun as possible. In July 2022, we launched our Pocket Champs game worldwide which quickly became one of the top-grossing games in its category. In our fast-paced, tech-driven environment, we continuously innovate by developing and updating our proprietary modules, along with integrating third-party ones, to enhance game functionalities, ensure precise analytics, and comply with evolving regulations. This dynamic ecosystem requires meticulous coordination to keep our games at the forefront of technology and user experience. Our Analytics team covers the full spectrum: a live game generating real revenue, several titles in active development, and a Data Core team building the infrastructure that powers everything. You won't be working in a silo, you'll be joining a connected team where what you build on Pocket Champs shapes how we think about analytics across the whole company. As Lead Data Analyst on Pocket Champs, you will be the senior analytical voice on our core game, defining what healthy looks like, challenging investment decisions with data, and setting the standard for how the analytics team thinks and operates. This role sits at the intersection of the game team: designers, PMs, and Live Ops, and the full technical backbone of Madbox: Data Core, Central Game Tech building cross-game functionalities, Web Tech developing new tools, and an AI team making everything smarter. You'll coordinate across all of them. Y our future responsibilities and scope: Shape the Game Strategy: Be the central analytics voice on Pocket Champs, define what healthy looks like, challenge investment decisions with data, and set the analytical direction for the game Lead the Analytics Standard: Elevate the bar for the team, set methodology standards, challenge analytical approaches, and mentor analysts on quality, rigor, and communication Own Experimentation: Own the A/B test framework end to end: design, evaluation methodology, and standards for how results are interpreted and acted on Design Data Access: Translate business questions into data model requirements and coordinate with the Data Core team to build the layers that power analytical work across the game Drive Product Insights: Proactively surface insights for the product team, not just answering questions, but identifying what questions should be asked Define Communication & Process: Set and own the standards for how analytical findings reach designers, PMs, and Live Ops: format, cadence, and whether it actually influenced decisions The profile we are looking for: 5+ years in mobile gaming analytics , worked on live games across the full release cycle, with direct experience in retention and monetization mechanics influencing outcomes Strong statistical foundations : designed and evaluated A/B tests end to end, and knows what to do when conditions aren't clean Track record of building KPI frameworks from first principles, defining what matters for the specific game and context rather than defaulting to industry convention Evidence-first: forms strong positions from data, defends them under pressure, but stays open to changing course when the evidence calls for it, the goal is to be correct, not just right. Able to translate complex data into clear, actionable insights for both technical and non-technical audiences Expert proficiency in SQL and either R or Python for data exploration and analysis High autonomy, low maintenance: figures things out quickly, meticulous about what matters, moves with pragmatism and proactivity Nice to have: Experience scaling games on revenue across different game types Familiarity with Bayesian methods Experience designing data models and metric layers, not just consuming dashboards and the ability to communicate those designs clear
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