Data Analyst | Mid-Senior | Saily

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We’re looking for a data-driven problem solver who can turn complex customer and product data into clear business opportunities. You’ll be comfortable digging deep into user behavior, spotting patterns across the customer lifecycle, and translating them into actionable insights for product and marketing teams. Strong analytical skills are key, but so is curiosity: we want someone who doesn’t just report what happened, but asks why it happened, what it means for the business, and what we should do next.

Team composition: 4 Data Analysts, 2 in Vilnius, 1 in Kaunas, one in Poland.

Interview process: 1st interview with a Talent Partner (45 minutes) -> Test task (several hours of work - with 1 week deadline) -> technical interview (60 min) -> final (45-60 min)

Main Responsibilities

• Define, track, and optimize key metrics and KPIs for product and marketing teams.
• Analyze users and products to find new business opportunities and areas for improvement.
• Develop and maintain automated reports and dashboards that provide visibility into customer behavior and product performance.
• Conduct deep-dive analyses on customer cohorts, segmentation strategies, and touchpoints to uncover growth and optimization opportunities.
• Build, support, and replicate data structures (including database structures, table building, reporting, data visualization, regression analysis, time series, etc.).
• Deliver clear, compelling presentations of data-driven insights to cross-functional stakeholders.
• Support the development and maintenance that enable scalable analysis (e.g. user segmentation, attribution modeling, funnel analysis).

Core Requirements

• 3+ years in a role as a data analyst;
• Solid understanding and experience of SQL (Google BigQuery as an advantage) and Python or R (for data modeling and general development);
• Familiarity with customer lifecycle frameworks and techniques for LTV, churn, retention, and cohort analysis.
• Strong experience with data visualization tools (e.g., Looker, Tableau, Power BI, or equivalent).
• Strong communication skills, a proactive approach, analytical problem-solving abilities, and a collaborative mindset, being an effective and versatile team player;
• Experience with Google Analytics;
• Proven experience with various data visualization and statistical analysis methods;
• Experience in e-commerce, SaaS, telecommunications, or digital marketing environments is a plus;
• Data Science/ML interest/affinity would be a plus.