About the role

The Product Analyst will build dashboards to monitor player behavior, retention, and monetization while performing cohort and funnel analyses. They will also design and execute A/B experiments and provide actionable insights to optimize live-ops and paid acquisition campaigns.

What they look for

SQL Data Analysis Tableau Looker Python R A/B Testing Mobile Gaming KPIs LTV Modeling AppsFlyer Adjust Singular BigQuery Snowflake Excel Google Sheets

Requirements

Candidates must have at least 5 years of experience in a data analyst role, preferably within mobile gaming or consumer apps. Proficiency in SQL and experience with BI tools and mobile attribution platforms are required.

Full description

Product Analyst

RESPONSIBILITIESPillar 1 · PLAYER BEHAVIOUR & RETENTION ANALYTICS

Build dashboards to monitor player health, retention, engagement, and churn.
Perform cohort, funnel, and player segmentation analyses to uncover behavioral insights.
Identify churn risks, engagement opportunities, and metric anomalies, delivering actionable recommendations to product and live-ops teams.

Pillar 2 · UA & PAID CHANNEL PERFORMANCE

Own UA performance reporting across paid channels, tracking acquisition, conversion, and ROAS metrics.
Build attribution dashboards and analyze campaign, channel, creative, and geo performance to drive optimization.
Deliver actionable post-campaign insights, monitor paid vs. organic trends, and identify top-performing creatives.

Pillar 3 · MONETISATION & REVENUE ANALYTICS

Track and report revenue across IAP products, geos, platforms, and player segments while monitoring core monetization KPIs.
Build LTV models, analyze IAP offer performance, and identify high-value payer segments to optimize monetization.
Reconcile platform revenue, investigate anomalies, and provide actionable insights to support monetization decisions.

Pillar 4 · LIVE-OPS & EVENT TRACKING

Own live-ops event tracking, ensuring accurate instrumentation and real-time performance monitoring.
Measure event impact on engagement, retention, and revenue through pre/post-event analysis and KPI tracking.
Maintain event performance history and deliver timely post-event reports with actionable recommendations.

Pillar 5 · A/B TESTING & EXPERIMENTATION

Design, execute, and analyze A/B and multivariate experiments across product, monetization, and store surfaces.
Ensure statistically sound testing by defining success metrics, validating test integrity, and delivering data-backed recommendations.
Maintain an experimentation backlog and log to prioritize, track, and scale high-impact learnings.

REQUIRED QUALIFICATIONS

5 years of experience in a data analyst or analytics role, preferably in mobile gaming or a consumer app environment.
Proficiency in SQL — able to write complex queries independently (joins, window functions, aggregations, subqueries).
Strong working knowledge of Excel or Google Sheets for ad-hoc analysis and reporting.
Experience with at least one BI or dashboarding tool: Tableau, Looker, Mode, or equivalent.
Familiarity with mobile attribution platforms: AppsFlyer, Adjust, or Singular.
Working knowledge of core mobile gaming KPIs across retention, UA, and monetisation.
Ability to independently scope an analytical question, structure an approach, and deliver a clear output with a recommendation.
Strong written and verbal communication — able to present findings to non-technical stakeholders without losing accuracy.

PREFERRED QUALIFICATIONS

Experience with Python or R for data manipulation, statistical analysis, or modelling.
Hands-on experience designing and analysing A/B tests with statistical rigour (confidence intervals, p-values, MDE calculation).
Familiarity with event-level data pipelines (e.g. Firebase, GameAnalytics, Amplitude, Mixpanel, or a custom CDP).
Experience building or maintaining LTV models for mobile games.
Knowledge of mobile game monetisation structures: IAP, subscriptions, battle passes, ad monetisation.
Exposure to live-ops analytics or seasonal event measurement.
Experience with cloud data warehouses: BigQuery, Snowflake, Redshift, or Databricks.

TOOLS & PLATFORMS

Query & Analysis: SQL (BigQuery / Snowflake / Redshift), Python / R (preferred) BI & Dashboards: Tableau / Looker / Mode / Google Data Studio Attribution: AppsFlyer / Adjust / Singular Event Analytics: Amplitude / Mixpanel / Firebase / GameAnalytics Store Consoles: App Store Connect, Google Play Console Paid UA (reporting): Meta Ads Manager, Google UAC, TikTok Ads, Apple Search Ads Spreadsheets: Google Sheets / Excel Project Management: Jira / Asana / Notion