Senior Product Analyst

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Job Description

Job Description
We are looking for a Senior Product Analyst to join the Player Value team on Candy Crush Saga. You will own the analytics and operational support that helps the team understand player behaviour, run better experiments, and make faster, sharper decisions. Your primary focus will most likely be the In-App Purchases (IAP) area, though the role may span other parts of the player journey — early funnel, communication systems, or the in-game economy — as priorities evolve.
This is a role for someone who is genuinely independent and analytically driven: comfortable owning the experimentation lifecycle end to end, partnering closely with Product Managers, translating messy data into clear recommendations, and rolling up their sleeves on operational work at Candy scale without balking at it. You will work cross-functionally every day and gain hands-on exposure to AI tools such as Claude, ChatGPT and Codex, which the team actively uses to accelerate analysis, reporting and communication.
Your Role Within Our KingdomOwn the experimentation lifecycle end to end for your area — from problem formulation and hypothesis design through analysis, readout, recommendation and follow-up.
Perform quantitative (and, where useful, qualitative) analysis of player behaviour to identify opportunities to improve monetisation, retention and player experience.
Turn complex data into clear insights, recommendations and narratives that Product Managers, Designers and leadership can quickly act upon.
Support pricing decisions by analysing price points, offers and promotions, measuring their impact on conversion, revenue and long-term player value.
Help manage the in-game economy by monitoring balance, sinks and sources, and the health of currency and reward systems while proactively identifying risks and opportunities.
Own tracking specifications by defining the events and metrics needed for new features, writing clear tracking documentation and ensuring instrumentation is implemented correctly so data is trustworthy from day one.
Take ownership of operational work at scale, including reporting, observability, data quality, event integrity and coordination, recognising these as essential parts of delivering value in a live game.
Build and maintain Looker dashboards and reporting frameworks that enable self-service analytics and faster decision-making.
Write robust, performant SQL in BigQuery to answer product questions and power analysis and reporting.
Partner closely with Developers, Product Managers and Data Scientists on end-to-end solution delivery, observability, experimentation and data model improvements.
Use segmentation, funnel analysis and journey mapping to explore complex product questions and uncover meaningful insights.
Use AI tools such as Claude, ChatGPT and Codex to accelerate analysis, prototyping and communication.
Support the Analytics craft through knowledge sharing, strong data definitions, shared standards and mentoring more junior analysts.
What Success Looks LikeYou become a trusted analytical partner to your Product Manager, helping shape product decisions through data, experimentation and commercial insight.
You provide reliable, actionable insights that improve product decisions and deepen the team's understanding of players.
You help the team move quickly by surfacing the right facts, reducing ambiguity and connecting data to product outcomes.
You operate effectively in a fast-paced live-game environment, solving problems that rarely come with predefined solutions or established playbooks.
You build strong, trusted relationships with Product, Design, Engineering and Analytics partners, contributing to high-quality end-to-end delivery.
Operational work at scale is executed reliably and efficiently because you treat it as a core part of delivering value rather than a maintenance task.
Skills to Create Thrills CoreStrong analytical and problem-solving skills, with a track record of deriving meaningful insights from behavioural or product data.
Strong SQL skills (BigQuery preferred) and confidence working independently with large datasets.
Experience owning or contributing to experimentation and A/B testing, including helping design experiments, interpreting results and translating findings into product recommendations.
Dashboarding experience in Looker (or a comparable BI tool) to build reporting and self-service analytics.
Experience using data to support product, business or operational decisions.
Ability to communicate analysis clearly and concisely through strong data visualisation and evidence-based recommendations.
Comfort working cross-functionally with Product, Design, Engineering and Data Science.
Genuine independence and initiative — comfortable taking ambiguous product problems and driving them through to actionable outcomes.
Willingness to take ownership of operational work at scale, including tracking, observability and data quality, recognising these as essential parts of delivering product v