Senior Games Data Analyst

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Games Data Analyst based in United Arab Emirates. This is a senior analytics role focused on turning complex player and product data into insights that improve engagement, retention, monetization, and overall player experience. You will work closely with Product, Game Operations, Marketing, CRM, Engineering, and other cross-functional teams to influence product and business strategy. The role combines advanced analytics, experimentation, statistical analysis, and business intelligence across the full player lifecycle. You will lead analytical projects, evaluate game features and campaigns, and establish reliable measurement frameworks for products and player segments. Your work will help identify growth opportunities, uncover risks, explain KPI changes, and guide data-informed decisions. You will also contribute to stronger data quality, tracking, analytical standards, and reporting practices across the organization. The environment is fast-paced and international, offering significant ownership and flexibility within a remote-first team. Accountabilities • Analyze player behavior across the complete 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, execute, and evaluate A/B tests and other experiments, including hypothesis development, sample-size estimation, metric selection, statistical testing, and interpretation of results. • Measure the impact and performance of game features, promotions, events, bonuses, and marketing campaigns. • Define, monitor, and maintain key product and gaming metrics across games and player segments. • Build dashboards, recurring reports, and analytical tools that enable stakeholders to monitor performance and make timely decisions. • Investigate significant or unexpected changes in KPIs, determine root causes, and assess their business impact. • Translate complex analytical findings into clear, actionable recommendations for both technical and non-technical audiences. • Partner with Product Managers and game teams to establish analytical requirements and measurement approaches before new features or initiatives are launched. • Collaborate with Data Engineers to improve data quality, tracking coverage, analytical datasets, and underlying data models. • Promote consistent analytical methodologies and standards across teams. • Encourage data-informed decision-making by communicating insights effectively and connecting analysis to business outcomes. Requirements • 5+ years of professional experience in data analytics, product analytics, business intelligence, or a related analytical discipline. • At least 3 years of experience in gaming, online entertainment, betting, financial quantitative research, or another high-volume digital product environment. • Advanced SQL skills and demonstrated 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, experimental design, and A/B testing methodologies. • Experience using Python or R for data analysis, statistical modeling, or automation. • Hands-on experience with BI and data visualization tools such as Tableau, Power BI, Looker, or Apache Superset. • Familiarity with cloud data warehouses such as Amazon Redshift, Snowflake, BigQuery, or Databricks. • Experience designing event tracking and validating data quality. • Strong analytical and critical-thinking skills, with the ability to turn ambiguous business questions into structured analysis and actionable recommendations. • Excellent communication and stakeholder-management skills, with the ability to explain analytical concepts clearly to diverse audiences. • Ability to manage multiple analytical projects independently while working effectively in a fast-paced environment. • Experience publishing statistics-related research in an SCI-indexed journal is a plus. • Strong attention to detail and a practical, business-oriented approach to data analysis. Benefits • Remote-first working environment. • Competitive salary with individual performance-based bonuses paid quarterly. • 28 days of paid annual leave. • Core working hours from 10:00 AM to 3:00 PM in your local time zone, with flexibility outside those hours. • Referral bonuses and flash bonuses. • Top-of-the-line professional equipment. • Annual company retreats offering opportunities for collaboration and internal networking. • Opportunity to work on large-scale gaming and digital product analytics challenges. • International, cross-functional environment with significant ownership and autonomy. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. 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5+ years of professional experience in data analytics, product analytics, business intelligence, or a related analytical discipline. At least 3 years of experience in gaming, online entertainment, betting, financial quantitative research, or another high-volume digital product environment. Advanced SQL skills and demonstrated 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, experimental design, and A/B testing methodologies. Experience using Python or R for data analysis, statistical modeling, or automation. Hands-on experience with BI and data visualization tools such as Tableau, Power BI, Looker, or Apache Superset. Familiarity with cloud data warehouses such as Amazon Redshift, Snowflake, BigQuery, or Databricks. Experience designing event tracking and validating data quality.

Analyze player behavior across the complete 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, execute, and evaluate A/B tests and other experiments, including hypothesis development, sample-size estimation, metric selection, statistical testing, and interpretation of results. Measure the impact and performance of game features, promotions, events, bonuses, and marketing campaigns. Define, monitor, and maintain key product and gaming metrics across games and player segments. Build dashboards, recurring reports, and analytical tools that enable stakeholders to monitor performance and make timely decisions. Investigate significant or unexpected changes in KPIs, determine root causes, and assess their business impact. Translate complex analytical findings into clear, actionable recommendations for both technical and non-technical audiences. Partner with Product Managers and game teams to establish analytical requirements and measurement approaches before new features or initiatives are launched. Collaborate with Data Engineers to improve data quality, tracking coverage, analytical datasets, and underlying data models. Promote consistent analytical methodologies and standards across teams. Encourage data-informed decision-making by communicating insights effectively and connecting analysis to business outcomes.