Data Analyst – Product

This is a fully remote position, open to applicants in Cyprus.

📋 Description

• Collaborate closely with Product, Commercial, and Engineering teams to gain insights into user behavior.

• Assess and formulate product hypotheses.

• Design and evaluate experiments.

• Enhance key business and product metrics.

• Establish scalable analytics foundations, including metrics, data marts, dashboards, and alerting systems.

• Examine user behavior and product journeys across both web and mobile applications, covering aspects such as funnels, activation, engagement, retention, monetization, and feature adoption.

• Recognize drop-offs, behavioral patterns, friction points, and growth opportunities, converting them into actionable product hypotheses.

• Analyze the impact of product launches and modifications, articulating what changed, why it changed, and for which users.

• Develop and prioritize hypotheses while defining measurable success criteria.

• Design and assess A/B tests and other experimental methods, considering primary metrics, guardrails, sample size, segmentation, and statistical interpretation.

• Convert experiment findings into clear product decisions and subsequent actions.

• Define and uphold product KPIs and metric trees with uniform definitions across teams.

• Create dashboards and analytical views for Product teams.

• Construct user and behavioral segmentations based on lifecycle stage, product usage, engagement, monetization, and additional characteristics.

• Analyze variations between user cohorts and segments.

• Define analytical and business requirements and engage in the development of product data marts and single-source-of-truth datasets.

• Collaborate with Engineering and Data Engineering on event tracking and instrumentation.

• Refine the product metrics system, including definitions, documentation, ownership, and consistency.

⛳️ Requirements

• Over 3 years of experience in data analytics (experience in fintech/product is a considerable advantage).

• Proficient in SQL and Python, with practical experience handling large datasets.

• Strong comprehension of product analytics concepts such as funnels, conversion, retention, cohorts, engagement, monetization, and segmentation.

• Practical experience with A/B testing and experiment analysis, including statistical significance, confidence intervals, guardrail metrics, and common biases.

• Familiarity with product analytics tools and event-based tracking.

• Ability to effectively communicate insights and collaborate with cross-functional stakeholders.

• Proficient in advanced Russian and English.

• Nice-to-have: Experience in building analytical data marts or working with dbt-style analytics engineering workflows.

• Nice-to-have: Experience managing event tracking across web and mobile applications.

• Nice-to-have: Knowledge of marketing analytics, acquisition, and attribution.

🏝️ Benefits

• Comprehensive benefits package.

• Opportunities for professional development and growth.

• Flexible working arrangements.