Our client is looking for a Middle Data Analyst.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Required Skills & Experience:
Technical skills:
34 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+).<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Interview process:
HR Interview with the Recruiter;
30-minute technical interview;
1.5-hour Final interview with the team;
Final decision.<\/p>\n
If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!<\/p>\n","protected":false},"excerpt":{"rendered":"
Our client is looking for a Middle Data Analyst. Role…<\/p>\n","protected":false},"author":14390,"featured_media":0,"parent":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_mo_disable_npp":"","rwu_salary_min":0,"rwu_salary_max":0,"rwu_salary_currency":"","rwu_salary_period":"","rwu_english_level":"B2","rwu_experience_months":36,"rwu_candidate_countries":"\u0412\u0435\u0441\u044c \u0441\u0432\u0456\u0442","rwu_company_type":"\u041f\u0440\u043e\u0434\u0443\u043a\u0442\u043e\u0432\u0430 \u043a\u043e\u043c\u043f\u0430\u043d\u0456\u044f","rwu_industry":"gambling","rwu_part_time":false,"rwu_source_views":63,"rwu_source_applications":11,"rwu_source_category":"Data Analyst","rwu_source_name":"Djinni.co","rwu_source_url":"https:\/\/djinni.co\/jobs\/851304-middle-data-analyst\/"},"job_category":[57],"job_type":[54],"class_list":["post-4040975","job","type-job","status-publish","hentry","job_category-programuvannia","job_type-povna-zainiatist"],"yoast_head":"\n