Product Analyst optimizing ARRISE’s iGaming products through KPI analysis, A/B testing, and player-behavior insights. Building dashboards and recommendations for product and game-design decisions.
Responsibilities
Partner with Product Managers and game designers to define, track, and evolve core product KPIs across the game portfolio
Design, run, and analyze A/B tests and product experiments
Conduct deep-dive analyses of player behavior and product usage to uncover trends, friction points, and opportunities
Apply statistical techniques including hypothesis testing, regression, and segmentation/clustering for forecasting and behavioral modelling
Build and maintain automated dashboards and self-serve reporting for product KPIs, feature adoption, and player experience metrics
Perform recurring analysis of product and feature performance across markets, operators, and product verticals
Translate quantitative findings into actionable recommendations for Product, Game Design, and Executive stakeholders
Support ad-hoc analytical requests related to product prioritization, feature launches, and roadmap decisions
Identify strengths and weaknesses in product performance and present findings to technical and non-technical audiences
Requirements
Bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field
5+ years of experience in a product analyst, data analyst, or similar analytical role
Experience in iGaming or online/mobile gaming is a strong advantage
Strong SQL skills with experience querying large, complex datasets — must have
Proficiency in at least one BI visualization tool (Tableau or Power BI) — must have
Practical experience designing and analysing A/B tests or product experiments, including hypothesis testing and interpreting results — must have
Working knowledge of statistical methods: regression, segmentation, and hypothesis testing applied to product and behavioural data
Strong analytical thinking, attention to detail, and a structured approach to problem solving
Excellent communication skills, with the ability to translate complex data into actionable recommendations
Ability to work independently and collaborate effectively as part of a cross-functional team
Business fluency in written and spoken English
Experience with Python (Pandas, NumPy) or R for data analysis and automation
Familiarity with product/event-tracking analytics tools such as Amplitude, Mixpanel, or Segment
Knowledge of data warehousing concepts and the modern data stack, including Snowflake, BigQuery, and dbt
Advanced Excel skills, including pivot tables and data modelling
Experience working in agile, cross-functional product teams
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