Data Analyst

At WinZO, our Data Analytics team transforms raw data into strategic advantage. We're a tight‑knit crew of analytical storytellers who blend SQL, Python, and modern BI tools to uncover user behaviors, optimize growth levers, and inform product strategy. From automated ETL pipelines to executive dashboards, we deliver insights that drive millions of microtransactions daily. Our culture of ownership and continuous learning ensures every analysis you craft moves the business forward.

What you will do: Design self‑service, drill‑down dashboards that surface real-time KPIs like engagement, retention, monetization, empowering teams to act instantly on data. Architect robust A/B‑testing platforms: define metric contracts, automate sample‑size calculations, and embed statistical checks to validate feature impact. Develop modular data pipelines using dbt and Airflow that ingest billions of event logs, enforce data quality checks, and deliver analysis‑ready tables. Produce polished presentations and summaries that turn complex cohort, funnel, and lifetime‑value analyses into clear, actionable business recommendations. Lead end-to-end analytics projects, from scoping and metric definition to pipeline implementation and stakeholder presentation. Design and deploy self‑service dashboards with embedded commentary, parameterized filters, and SLA‑driven alerting. Architect experimentation infrastructure, ensuring proper power analysis, sequential testing, and uplift modeling. Mentor junior analysts, conduct code reviews for SQL style and BI best practices, and host knowledge‑sharing sessions. Partner with data engineering to optimize upstream pipelines for latency, freshness, and data‑quality guardrails. Perform deep cohort, funnel, and retention analyses, quantifying the impact of product changes on user lifecycle and revenue.

Relevant years of hands-on experience in analytics, with expert SQL and Python (pandas) skills. Proficiency in a BI platform, building complex dashboards with advanced calculations and visualizations. Solid grounding in statistical methods: regression, survival analysis, and causal inference basics. Experience constructing and automating ETL pipelines (dbt, Airflow) under version control. Demonstrated ability to guide stakeholder alignment and deliver insights within agile sprints.