I am a data analyst with more than 3 years of experience in iGaming and product analytics, with a strong focus on retention, churn, LTV, cohort analysis, A/B testing, event analytics, dashboards, and analytics infrastructure.
I have worked extensively with SQL, Python, PostgreSQL, BI tools, API integrations, Docker-based workflows, and AI agents to automate analytical tasks and improve reporting efficiency.
In my recent roles, I analyzed user behavior in online casino products, built dashboards and data marts, automated reporting, and helped improve 30-day retention through experimentation and data-driven insights.
I also have experience as a data scientist, where I prototyped multi-agent LLM workflows, built RAG/vector-search pipelines, and designed knowledge-graph solutions for analytics, monitoring, and investigation use cases.
I enjoy translating business questions into clear metrics, experiments, and dashboards, and I am comfortable collaborating with both technical teams and business stakeholders.
Outside of work, I value a calm and disciplined lifestyle and keep active by training at the gym.
Analyzed user behavior in online casino products, including churn prediction and survival analysis; developed dashboards and reporting; created data marts and automated reporting; documented analytical processes; worked with SQL, Jupyter, Jira API, Kotlin/Timber logging, Docker, and AI agents.
Prototyped AI-agent workflows for analytics, retention, churn, fraud/risk monitoring, and automated reporting; built multi-agent LLM architecture; developed RAG/vector-search pipelines; designed knowledge-graph workflows; worked with Python, SQL, FastAPI, MariaDB, Redis, Docker, LLM APIs, embeddings, and streaming analytical interfaces.
Analyzed retention, LTV, churn, and player segments; built Tableau dashboards for marketing, product, and finance teams; ran A/B tests; conducted financial analytics; worked with PostgreSQL and optimized ETL processes.
Applied Mathematics
Higher Education
Data Analyst
Additional training
Deep Learning Model Development
Additional training
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