Moonfrog Labs - Lead Data Analyst - Python/Big Data in Bangalore, भारत

Senior/Lead Data AnalystAbout Moonfrog:Moonfrog was founded in 2013 with the purpose of making mobile gaming easy and fun. Breathing life into classic, evergreen games has been our forte, and we believe the best kind of games are ones that provide genuine and long-lasting engagement and delight, not just a way to pass time. Moonfrog has been able to constantly push out entertaining games at regular intervals since its inception, while being profitable at the same https://jobeax.com/link/MSHQ0gJEwPerCSpe's success is owed in a great deal to its unique product and engineering capabilities that help deliver superior gaming experiences. We continue to explore newer spaces in the gaming industry, leveraging our expertise in South Asia to bring equally popular and well-loved games to other parts of the https://jobeax.com/link/va050VbVzYTBaDqp February 2021, Moonfrog became part of the Stillfront group, which is a free-to-play powerhouse of gaming studios. Stillfront's main markets are within Europe, the US and the MENA region. SFG is headquartered in Stockholm, Sweden, and the company is listed on Nasdaq https://jobeax.com/link/WhdZkRW6gn8yua1G the business problem, not the https://jobeax.com/link/srqKa1lDevKJqRwZ games are played by millions of people daily. Every session leaves a trail: a level attempted eleven times, a bundle ignored, a player who quietly stopped opening the app on a Tuesday. Billions of these events land in our warehouse each month - and some of them are the difference between a game that grows and one that doesn'https://jobeax.com/link/RVxxP9BdbLGYFm8Z're looking for a Lead Data Analyst who wants to be handed a problem rather than a query request. You'll decide what's worth investigating, build the models and pipelines to investigate it, and defend the decision in front of https://jobeax.com/link/ZCp06r3j1eabf1Iy You'll Do:- Go deep, not wide. Run in-depth analyses that end in a decision: funnel drop-offs, cohort behaviour, segment deep-dives, feature post-mortems. Own the "why," not just the dashboard.- Own the churn numbers. Know retention and churn cold - by cohort, level, segment, geo. Build churn prediction that fires early enough for an intervention to exist, then prove the intervention moved the metric.- Predict player value. LTV and revenue forecasting the business can plan against - robust to seasonality, cohort mix, and content cadence.- Tune the economy. Sources and sinks, currency inflation, reward-event faucets, bundle pricing and elasticity. Catch drift before players do.- Understand paying and non-paying players. What separates them behaviourally, where the conversion moment actually sits, and what it means for pricing and content.- Run experimentation properly. Design and analyse A/B tests: sizing and power up front, guardrail metrics, and the integrity to call a flat result flat.- Own the data. Architect and optimise pipelines connecting game telemetry, the warehouse, and ML systems. Data quality, definitions and cost are yours, not just the final chart.- Make leadership fluent. Turn analysis into narrative for Product and Engineering leadership - and hold up under challenge.- Build self-serve and mentor. Dashboards (Metabase/Looker/Tableau) that answer the recurring questions, and a team of analysts you're actively raising the bar https://jobeax.com/link/i23gEwG68k1qixlJ We're Looking For:- 7 - 10 years in data analytics, ideally gaming, consumer tech, or mobile apps.- Mastery of SQL - non-negotiable. This is the core of the job. Window functions, complex joins across billions of rows, query optimisation, and the discipline to write SQL someone else can read six months later. Most of your answers will start here.- Strong Python for analysis and automation - pandas/numpy, scripting, and pipeline work.- Judgment about Gen AI. You use LLMs where they earn their place - boilerplate SQL, code review, drafting, summarising qualitative data, exploratory scaffolding - and you don't where they don't: numbers you'll present, causal claims, anything you can't verify. You know the difference between a fast answer and a correct one, and you check.- Big data and pipelines: Redshift, Athena, BigQuery, Hive or Spark, plus orchestration.- Real statistical foundations: experiment design, causal inference basics, quantitative modelling you can explain to a sceptic.- Ownership: projects driven end-to-end, and people made better along the way.- Education: Bachelor's or Master's in CS, Engineering, Statistics, Mathematics or similar.- Visualisation: Looker, Tableau, Metabase or Power https://jobeax.com/link/ITmH3oi2bCKHsPzA Points:- Mobile gaming analytics - retention curves, in-game economy, monetisation, LiveOps.- Experience standing up an experimentation platform or feature store.- Anything you've shipped that changed a game design https://jobeax.com/link/9bfdxG0qWVNM0NNy you've ever been frustrated that your best analysis ended in a slide instead of a shipped change - this is the other kind of job. (ref:hirist.tech)