Senior Games Data Analyst (Europe, Asia)

Sporty Group; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Remote-first company

Flexibility with hours

Competitive salary

Quarterly bonuses

Annual company retreats

Zusammenfassung

Sporty is seeking a Senior Games Data Analyst to transform player and product data into actionable insights that drive engagement, retention, and monetization. You will partner with Product Managers, Game Operations, Marketing, CRM and Engineering to lead analyses and establish reliable measurement frameworks.

You will design experiments, build dashboards, and translate complex findings into clear recommendations for stakeholders. Remote-first with flexible hours and quarterly bonuses.

Qualifikationen

• 5+ years of experience in data analytics
• 3+ years in gaming or high-volume digital products
• Experience with SQL and large-scale datasets
• Strong knowledge of product and gaming metrics (DAU/MAU, ARPU, LTV)
• Experience with Python or R for data analysis
• Experience with BI and visualization tools (Tableau/Power BI/Looker)
• Excellent communication and stakeholder management skills
• Ability to manage multiple projects in a fast-paced environment
• Familiarity with cloud data warehouses (Redshift/Snowflake/BigQuery/Databricks)
• Experience with event-tracking design and data-quality validation

Aufgaben

• Analyze player behavior across lifecycle stages (acquisition to reactivation)
• Perform segmentation, funnel, cohort, retention, and churn analyses
• Design and evaluate A/B tests and experiments
• Measure performance of features, promotions, events, and campaigns
• Define KPIs and analytical frameworks for different games
• Build dashboards and recurring reports for stakeholders
• Investigate KPI anomalies and determine business impact
• Translate findings into actionable recommendations for technical and non-technical audiences
• Collaborate with PMs and game teams to define analytical requirements
• Work with Data Engineers to improve data quality and modeling

Kenntnisse

SQL

Python/R

BI tools

A/B testing

Statistics

Data visualization

Communication

Stakeholder management

Project management

Cloud data warehouses

Tools

Tableau

Power BI

Looker

Apache Superset

SQL

Python

R

Redshift

Snowflake

BigQuery

Jobbeschreibung

About the role

We are looking for a Senior Games Data Analyst to transform player and product data into actionable insights that improve player experience, engagement, retention, and monetization. In this role, you will partner closely with Product Managers, Game Operations, Marketing, CRM, and Engineering teams. You will lead analytical projects, evaluate game features and promotional activities, establish reliable measurement frameworks, and provide data-driven recommendations that influence product strategy and business decisions.

What you'll be doing

• 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.
• Promote consistent analytical standards and encourage data-informed decision-making across the organization.

What you'll bring

• 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.
• Having published statistics-related research in an SCI-indexed journal is a plus.
• 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.

What's in it for you

Sporty is a remote first company in pursuit of sustainability A competitive salary + individual performance based bonuses every quarter 28 days paid annual leave Our core working hours are 10am-3pm in your local time zone with flexibility outside of this Referral bonuses & flash bonuses Top of the line equipment Annual company retreats to provide great internal networking opportunities

Interview Process

• Remote video screening with our Talent Acquisition Team
• Offline Take home assignment
• Remote video interview with Team Members (3x45 Mins)