Background
We are building the next-generation Social Gaming & AI platform for the world — where users can swipe and instantly play thousands of mini-games, chat or voice with friends, engage in PK battles, and co-create interactive content.
By integrating AI-driven personalization and creation tools, we’re creating a new social ecosystem that blurs the line between playing, sharing, and creating.
About the Role
We are not looking for someone who just measures numbers — we’re looking for someone who understands why the numbers move. As our Data Intelligence Analyst, you will bridge data science, behavioral psychology, and design, uncovering the cause-and-effect patterns that drive user growth, retention, and monetization.
Your mission: move beyond dashboards and correlations to discover the underlying levers of user behavior — the interventions that actually change outcomes.
If you’ve ever asked “Why did this work?” or “What would have happened if we didn’t run that event?”, you’ll feel right at home here.
Key Responsibilities
• Causal Insight Generation – Design and conduct causal analyses (A/B tests, quasi-experiments, and observational studies) to understand the drivers behind player engagement, retention, and revenue.
• Behavioral Analysis – Decompose player journeys using causal frameworks (DAGs, counterfactual thinking, intervention modeling) to pinpoint what actions create lasting value.
• Experimentation Partner – Work with product, growth, and live ops teams to design experiments that identify true lift, not just correlation.
• Strategic Storytelling – Translate complex causal findings into clear narratives and growth strategies. Help leadership move from “what happened” to “why it happened” and “what to do next.”
• Cross-Functional Collaboration – Partner with marketing and product to test hypotheses, evaluate new features, and optimize player funnels through data-driven interventions.
• End-to-End Ownership – From hypothesis framing → data modeling → interpretation → communication — you’ll own the complete analytical lifecycle.
What We’re Looking For
• 1-5 years of experience in data analytics, business intelligence, or product analytics.
• Strong command of SQL and experience with analytical scripting languages (Python, R, or similar).
• Practical understanding of causal inference concepts — such as experiments, control groups, confounders, or counterfactual reasoning — even if you haven’t formally studied them.
• Experience designing or evaluating A/B tests, incrementality studies, or campaign lift analyses.
• Ability to think in causal graphs (DAGs) — not just KPIs — to explain why metrics move.
• Strong communication and data storytelling skills: you can translate causal findings into clear product or growth actions.
• Curiosity-driven mindset: you instinctively ask “why” before “what.”
Nice to Have
• Experience in gaming, social platforms, or consumer entertainment analytics.
• Familiarity with causal inference libraries (DoWhy, EconML, CausalML, PyMC, or similar).
• Knowledge of AARRR metrics (Acquisition, Activation, Retention, Revenue, Referral) and how causal drivers affect each stage.
• Understanding of player psychology and in-game economy dynamics.
• Exposure to lift measurement, churn prediction, and viral loop modeling.
What We Offer
• The chance to define why our players stay, pay, and play — not just how many do.
• A high-impact seat at the table: your analysis will directly shape game design, growth strategy, and monetization experiments.
• A collaborative environment where data and causality thinking guide every decision.
• Direct access to leadership and product decision-makers.
How to Apply
Send your resume and (optionally) a short portfolio, experiment write-up, or dashboard sample to hr@Mozat.com
