Lead Data Analyst
Animoca Brands is a Hong Kong-founded digital-assets company that builds Web3 and AI products, provides digital-asset services, and manages a portfolio of more than 600 investments.
Maintainer signals as of 9/25/2026
Funding history
Projects
About Animoca Brands
Animoca Brands Corporation Limited operates across three integrated pillars: building consumer and institutional Web3 businesses, providing digital-asset advisory and infrastructure services, and managing investments across more than 600 companies and digital assets. Its current projects include digital identity, education infrastructure, blockchain gaming, AI agents, and tokenized real-world assets.
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