Data Analyst (Acquisition)

Skills

About the Role

You will join a small analytics squad that works like a shared force for the business. Your home base is the Acquisition block: Affiliate, CRM, Web and Marketing, with Affiliate as your main area. This is not a pull-a-ready-report role. You scope what needs measuring, build and model the data yourself, run the analysis and bring clear recommendations to the stakeholders who own each area. As the squad grows, its coverage extends to new areas such as finance and logistics, so the team stays useful across the whole business.

Requirements

• 3+ years in analytics (data, business, or product), with examples where your work changed a real decision.
• Solid technical and statistical grounding. You frame the question, pick the right method, and read results honestly. A quantitative or engineering background is a plus.
• You build, not just consume. Comfortable pulling and modeling data from raw sources, and going deep when a problem calls for it.
• Core tools: strong SQL and Python, a data warehouse (BigQuery or Postgres), and a BI tool (Power BI, Looker, or Tableau).
• Product and web analytics: GA4, Amplitude, or similar.
• Clear communicator who works directly with stakeholders, and practical about precision: you know when a rough answer is enough and when a number must be exact.
• Nice to have: E-commerce, crypto, or fintech; Affiliate or partner programs, promo-code or marketing attribution; CRM analytics; Ad platforms such as Google Ads and Meta Ads, especially their reporting and attribution data; Familiarity with Tangem Wallet or similar applications; Business sense that ties metrics to growth and revenue.

Responsibilities

• Start with affiliate analytics (your main area). Own the numbers for the affiliate and promo-code program: partner performance, payout logic, and ROI.
• Take on more as you grow. Expand into CRM, web, and marketing analytics, focusing on the questions that matter most to the business.
• Build your own datasets. Pull and model data from raw sources when ready-made tables and dashboards are not enough.
• Find what matters in the data. Use statistics to tell real changes from noise, and explain what moved and why.
• Deliver dashboards and recommendations. Build self-serve reporting, and turn the analysis into clear next steps for the people who own each area.
• Use AI sensibly to work faster, knowing where it helps and where it does not.

Benefits

• Stability, development, participation in the future unicorn's growth
• Remote work from anywhere in the world, with a schedule aligned with GMT+3
• Competitive salary in EUR/USDT
• Unlimited vacation
• Birthday presents
• Compensation for the purchase of necessary technical devices for the work
• Paid sick leave