Tokenomics Analyst

3 Months ago • All levels

Job Summary

Job Description

Animoca Brands seeks a Tokenomics Analyst to advise partners on token economy design. Responsibilities include identifying stakeholders and their interactions, designing token utility, governance, and security, modeling token allocation, and contributing to litepapers/whitepapers. Collaboration with internal teams (Listing, Engineering, Treasury, Game Development) is crucial for successful implementation. The role also involves supporting existing token economies, identifying partnerships, conducting research on token economies, and codifying best practices. The ideal candidate possesses a Master's or PhD in a quantitative field, deep Web3 knowledge, and experience in token economy design or writing litepapers/whitepapers. Strong analytical and communication skills are essential.

Must have:

Master's/PhD in quantitative field
Deep Web3 knowledge
Token economy design experience
Strong analytical & communication skills

Good to have:

Litepaper/whitepaper writing experience
Modeling & simulation skills

3 skills required

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Job Details

Animoca Brands (ACN: 122 921 813), a Deloitte Tech Fast winner, a Fortune Crypto 40 company, one of the Top 50 Blockchain Game Companies 2024, and one of the Financial Times’ High Growth Companies Asia-Pacific 2023, is a Web3 leader that leverages blockchain to deliver digital property rights to consumers around the world to help to establish the open metaverse. The company develops and publishes a broad portfolio of products including Anichess, The Sandbox, PHANTOM GALAXIES™, and Crazy Defense Heroes, and products utilizing popular intellectual properties such as The Walking Dead and Power Rangers. One of Animoca Brands’ flagship projects is Mocaverse, a platform that enables consumers to maximize their Web3 exposure to experiences and rewards with a single login entry point. Animoca Brands is one of the most active investors in Web3, with a portfolio of over 540 Web3 investments, including Yuga Labs, Axie Infinity, Polygon, Consensys, Magic Eden, OpenSea, Dapper Labs, Yield Guild Games, and many more. For more information visit www.animocabrands.com or follow on X (Twitter), YouTube, Instagram, LinkedIn, Facebook, and TikTok.

Job Scope

The main scope of this role is to advise our partners and companies on token economy design. You will become the go-to expert in Tokenomics at Animoca Brands and help spearhead the transition of brands to Web 3.0

Responsibilities:

You will be an integral part of the Tokenomics team that works with companies both in and outside of Animoca Brand’s ecosystem on token economy design, including:

- Identify key stakeholders and their “sinks” and “faucets”

-Design token utility, governance, and security

- Model token allocation, distribution, and vesting schedules

- Contribute to litepapers/whitepapers

You will collaborate with different teams i.e., Listing, Engineering, Treasury, Game Development to ensure successful implementation of token economies
You will support and iterate existing token economies of Animoca Brands over time to ensure sustainability and growth
You will help identify potential partnerships with companies within Animoca Brands’ ecosystem and make appropriate introductions
You will perform research on different token economies to gather a fact base and help the team stay on top of the latest developments
You will help to codify best practices and optimize internal processes to scale the Tokenomics team further

Requirements / Skill Sets:

Master’s or pH.D. degree in Computer Science, Mathematics, Economics, or similar quantitative/research background
Deep interest and knowledge of Web 3.0 and blockchain is a must – crypto, NFTs, DAOs
Experience in designing token economies or writing litepapers/whitepapers (not a must but highly preferred)
Skilled at modelling and comfortable with building complex spreadsheets/simulations or computer models (not a must but preferred)
Highly motivated self-starter and fast learner
Excellent verbal and written communication skills

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