Product Analyst

November 3, 2026

Remote

Middle

Dubai, Yerevan, London, Belgrade

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Crypto or web3 project

Description

A Telegram-native all-in-one crypto app used by tens of millions of people worldwide is looking for a Product Analyst to own the analytical layer behind its product and operations teams. The role covers building and documenting data marts, dashboards, metrics, funnels and A/B test results, working closely with product managers, engineers and business stakeholders. The analyst also applies LLMs in day-to-day analytical workflows and handles ad hoc research requests.

Responsibilities

Create and enhance dashboards, reports, and systems for monitoring key metrics
Explore the company's data sources and document data marts, metrics, and relationships between entities
Establish consistent definitions of business metrics and contribute to the development of data governance practices
Conduct product analytics: define and track funnels, retention, activation, and engagement metrics, evaluate A/B tests and feature launches, and turn findings into recommendations for product teams
Apply LLMs in analytical workflows: use AI assistants for data exploration, documentation, and report drafting, and build reusable context
Conduct ad hoc research and handle urgent analytics requests from business stakeholders
Collaborate with analysts, developers, data engineers and product teams

Requirements

3+ years of experience as a Data or Product Analyst
Strong SQL skills including complex queries, CTEs, window functions, aggregations, and query optimization
Experience designing and building data marts
Experience working with BI tools and creating dashboards
Solid understanding of product analytics: funnel, cohort, and retention analysis, unit economics, and the design and statistical evaluation of A/B tests
Experience with event-based analytics using tools such as Amplitude, Mixpanel, or similar, with the ability to translate product questions into measurable metrics
Hands-on experience using LLMs such as ChatGPT, Claude, Copilot, or similar in day-to-day analytical work, with the ability to verify their output
Ability to create context for LLMs: structured descriptions of data sources, metrics, and business logic, well-crafted prompts, and reusable templates
Ability to explore unfamiliar datasets and understand their business context
Ability to independently manage tasks from initial requirements through to the delivery of a complete analytical solution