Senior Games Data Analyst
New
S
SportyGaming, Data Analytics
Europe, Asia, Core working hours are 10am-3pm in your local time zoneFull-TimeSenior
SalaryA competitive salary + individual performance based bonuses every quarter
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years of experience in data analytics, product analytics, business intelligence, or a related field; 3 years of experience in gaming, online entertainment, betting, or financial quantitative research
- Required Skills
- PythonSQLMicrosoft Power BITableauProduct AnalyticsA/B testingLookerR
Requirements
- 5+ years of experience in data analytics, product analytics, business intelligence, or a related field.
- At least 3 years of experience in gaming, online entertainment, betting, or financial quantitative research, or another high-volume digital product environment.
- Advanced SQL skills and experience working with large-scale datasets.
- Strong understanding of product and gaming metrics, including DAU/MAU, retention, churn, conversion, ARPU, ARPPU, payer rate, LTV, and player value.
- Solid knowledge of statistics, hypothesis testing, experiment design, and A/B testing.
- Experience using Python or R for data analysis, statistical modelling, or automation.
- Experience with BI and visualization tools such as Tableau, Power BI, Looker, or Apache Superset.
- Strong analytical thinking and the ability to move from a business question to a structured analysis and actionable recommendation.
- Excellent communication and stakeholder-management skills.
- Ability to manage multiple projects and work independently in a fast-paced environment.
- Familiarity with cloud data warehouses such as Amazon Redshift, Snowflake, BigQuery, or Databricks.
- Experience with event-tracking design and data-quality validation.
Responsibilities
- Analyze player behavior across the full lifecycle, including acquisition, onboarding, engagement, retention, monetization, churn, and reactivation.
- Identify opportunities and risks through player segmentation, funnel analysis, cohort analysis, retention analysis, and behavioral pattern analysis.
- Design and evaluate A/B tests and other experiments, including hypothesis development, sample-size estimation, metric selection, statistical testing, and result interpretation.
- Measure the performance of game features, promotions, events, bonuses, and campaigns.
- Define and maintain key product metrics and analytical frameworks for different games and player segments.
- Build dashboards and recurring reports that allow stakeholders to monitor product performance and make timely decisions.
- Investigate unusual changes in KPIs and determine their underlying causes and business impact.
- Translate complex analytical findings into clear recommendations for both technical and non-technical stakeholders.
- Partner with Product Managers and game teams to define analytical requirements before launching new features or initiatives.
- Work with Data Engineers to improve data quality, tracking coverage, data models, and analytical datasets.
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