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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 of experience as a Data Analyst, with hands-on experience applying machine learning to customer data, such as churn or propensity prediction, model-based segmentation, or LTV forecasting.
- Preferably, experience in customer analysis, including lifecycle, retention, cohort, churn, and LTV analysis.
- Proven experience building and evaluating customer segmentations, both rule-based and model-based (e.g. clustering), and turning insights into actionable recommendations for Product and Marketing teams.
- Experience designing and analysing experiments (A/B tests), including sample size calculation, significance testing, and translating results into clear recommendations.
- Solid SQL skills (Google BigQuery is an advantage) and Python experience for modelling (pandas, scikit-learn, or similar).
- Strong statistical foundation, including regression, hypothesis testing, and time series analysis.
- Experience with data visualisation tools (Looker preferred; Tableau, Power BI, or equivalent also fine) and the ability to present insights clearly to non-technical stakeholders.
- An independent and proactive working style. You take ownership, find information yourself, and are comfortable with ambiguity and frequent product changes.
NICE TO HAVE
- Experience with Google Analytics.
- Background in e-commerce, SaaS, telecommunications, or digital marketing.
- Experience in a startup or fast-paced product environment.
WHAT WE OFFER
- Sharpen your edge: training, mentorship, and room to grow — always.
- Take the time you need: extra vacation days, sick days, and time off when life calls.
- Get premium healthcare: private health insurance in Lithuania and Poland — fully covered.
- Protect your peace: enjoy free subscriptions to Calm, Headspace, and Mindletic, and our own resilience and mindfulness trainings.
- Own your fitness: in-house gyms, sport cards, online workouts, and personal guidance — on us.
- Pack your bags for workation: experience our company-wide trip abroad to the…