Data Scientist/Gaming Economist

We have built GAMEE as a high-engagement mobile gaming platform where players compete in skill-based tournaments to earn prizes for their activities. 20.000.000+ players registered on GAMEE so far and every month, they play over 40.000.000 gameplays across more than 80 games.

We introduced new blockchain gaming app Arc8 allowing players to earn $GMEE tokens and we have released G-Bots - unique collectible, playable and upgradeable game characters - in the form of non-fungible tokens (NFTs). What you earn, you own, so that you can use it, keep it to grow in value, trade it, sell it!

Our mission is to recognise and reward gaming skill, effort, and loyalty. A true Play-to-Earn.

We are now are hiring for a Game Economist/Data Scientist to join our expanding team.

The role would be ideal for a game enthusiast who can deconstruct and design game economies, understands data and is able to create and simulate scenarios for the evolution of complex systems in time.

We know it sounds complicated and we don’t expect you to check all the boxes - we just need you to be willing to learn!

As the Game Economist, you are responsible for managing the processes of token creation, design, development, go-to-market and operations.

The knowledge and skills you will gain will be highly demanded as tokens reach mainstream adoption.

Here’s how you’ll contribute:

• Analyze existing games and gaming projects


• Prepare models and simulations for new projects


• Analyze the impact of deployed changes and new features on the overall economy


• Work closely with a team of experienced game developers and NFT team


• Work on cool games with millions of players world-wide

A bit about you:

• You are plugged into the blockchain and specifically Gaming world. You need to know what is happening, what is working and not working


• You have a strong grasp of financial principles, such as liquidity and why it is important


• Must have a strong finance background, Bachelors and Masters in Math/Economics


• Degree in mathematics, statistics, or similar field (or strong professional experience in this area)


• Experience in statistical modelling


• Ability to work with large datasets


• Reliability, honesty, and independence