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Lead Data Analyst

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Страна
China
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Описание вакансии

TL;DR
Lead Data Analyst (Product Analytics/AI): Owning product, retention, acquisition, transaction, and subscription metrics while turning product and commercial data into recommendations, measurement frameworks, and reporting with an accent on unit economics, cohort analysis, experimentation, and AI-assisted analysis. Focus on diagnosing business performance, evaluating market opportunities, building self-service dashboards, and communicating actionable findings to product, growth, leadership, and the board.

Lead Data Analyst

Company

Animoca Brands

Conditions

6 days ago

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will own core product, retention, acquisition, transaction, and subscription metrics. You will diagnose business performance, build measurement for major releases, assess market opportunities and experiments, establish recurring reporting and self-service dashboards, and translate analysis into clear recommendations for product, growth, leadership, and the board. You will use AI to accelerate analysis and automate repetitive work.

Requirements

  • Commercial analytical thinking grounded in unit economics, payback periods, cohort analysis, and lifetime value
  • SQL proficiency
  • Product or behavioral analytics expertise
  • Modern data stack expertise
  • Python or a similar scripting language
  • Experience leading retention, growth, or monetization analysis for consumer products
  • Experience using AI tools for analysis and evaluating model-output reliability
  • Ability to communicate clear recommendations to non-technical audiences

Responsibilities

  • Own core activation, retention, active-user, acquisition-cost, transaction, and subscription metrics
  • Turn product, billing, and engagement data into business recommendations
  • Build measurement frameworks and impact analyses for major launches
  • Evaluate market opportunities, set goals, and run experiment-and-learn loops
  • Establish daily and weekly reporting and self-service dashboards
  • Present clear, actionable analysis to product, growth, leadership, and the board
  • Use AI for querying, summarization, prototyping, and automation

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