Middle Data Analyst

Role Overview:
We’re looking for an experienced Middle Data Analyst to join analytics team in the iGaming industry. You’ll take ownership of complex analytical tasks, drive data- informed decisions across multiple business functions, and serve as a go-to expert for data quality, player behaviour analytics, and reporting. If you have a solid background in gambling analytics and love working with large datasets, we want to hear from you.

Key Responsibilities:
Design and own end-to-end analytical workflows in Amazon Redshift — complex multi-step SQL: window functions, CTEs, large-scale joins, and performance tuning;
Conduct deep-dive player behaviour analyses: segmentation, RFM modelling, cohort analysis, LTV forecasting, and churn prediction;
Analyse A/B test results — interpret statistical significance, evaluate group comparability, identify confounding factors, and deliver clear recommendations to stakeholders;
Track and analyse iGaming KPIs — GGR, NGR, bonus abuse index, deposit/withdrawal trends, player LTV, and churn — proactively flagging anomalies;
Integrate and actively apply AI tools into day-to-day analytical work: prompt engineering, AI-assisted SQL generation, automated insight summarisation;
Translate complex data findings into clear, actionable outputs for non- technical stakeholders via Excel reports and presentations;
Learn and work in EasyMorph for reporting and data preparation tasks as part of team onboarding.

Required Skills & Experience:
Technical skills:
3–4 years of hands-on experience as a Data Analyst in iGaming or online gambling — mandatory;
Advanced SQL in Amazon Redshift — window functions, CTEs, subqueries, query optimisation, and working with large-scale datasets;
Experience with BI tools (Power BI, Tableau, Looker, or similar) - working with dashboards and using them to extract insights;
Proficiency in Excel: advanced pivot tables, vlookups and executive-level reporting;
Strong command of iGaming KPIs: GGR, NGR, player LTV, churn rate, bonus abuse metrics, deposit/withdrawal volumes;
Solid understanding of A/B test analysis — interpreting p-values, confidence intervals, and effect sizes; experience evaluating pre-test group balance and flagging randomisation issues;
Practical use of AI tools in analytical workflows: LLMs for insight generation, AI-assisted querying, prompt engineering for data tasks;
Strong data quality mindset — ability to sense-check numbers, investigate inconsistencies, and ensure analytical accuracy;
Clear English communication, written and verbal (upper-intermediate+).
Nice to Have:
Familiarity with Amazon QuickSight: navigating dashboards, using built-in features (Q / flow), filters, and calculated fields;
Exposure to EasyMorph or similar ETL/data preparation platforms.
Soft Skills:
High ownership and autonomy — you manage your tasks end-to-end without hand-holding;
Structured analytical thinking — you break down ambiguous business questions into clear data problems;
Proactive communication — flagging anomalies, pushing back on flawed assumptions, and keeping stakeholders aligned;
Ability to manage multiple priorities and deliver under deadlines in a fast-paced environment;
Collaborative mindset — comfortable working across teams and supporting junior colleagues.

The company guarantees you the following benefits:
A positive workplace atmosphere that creates a culture of collaboration and support, making it a place you'll love working in;
Competitive compensation and regular career development reviews;
Flexible working hours and remote working options, you'll enjoy the freedom that the company provides;
A generous vacation and sick leave policy, allowing you to take time off and enjoy a work-life balance;
Financial assistance for professional development, helping you stay ahead of the curve and love your career path;
Educational Allowances that give you the opportunity to expand your knowledge and experience;
You'll have a monthly allowance for personal activities, giving you the opportunity to pursue your interests and hobbies outside of work;
A comprehensive health insurance plan, depending on your current location;
Referral program with financial rewards for bringing top talent to the company;
Engaging in team-building activities and corporate parties.

Interview process:
HR Interview with the Recruiter;
30 minutes’ technical interview;
1.5-hour Final interview with the team;
Final decision.

If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!