Job Description - Reward Economy Lead (all genders)
We are seeking a talented and experienced Game Economy Designer to join our team. This is a unique opportunity for any economy designer where you get to merge your experience in game economy balancing with real money rewards. All this happens within an ad revenue based ecosystem of owned and operated casual games with an innovative play to earn app meta-layer touching millions of players in a first and very high impactful role.
We pay out millions of dollars each month as reward to players of our games, and are seeking our first Reward Economy Lead to design and help us develop the ideal balance of rewards and earnings. Your goal will be to drive engagement, retention, and revenue, all while maintaining a fair and sustainable ecosystem that does not charge users to play our games. We believe we are the only ones doing this at such a large scale right now!
Design and manage the rewarding and earning experience from an economic perspective for our players, forecasting player behaviors across both a casual game and a play to earn app layer
Craft and refine earning and rewarding loops, determining how players engage with them driving retention across the ecosystem balancing the challenges of an ad revenue based business model and an ecosystem of many individual games
Continuously enhance ecosystem performance through the creation and analysis of A/B tests of rewarding and earnings logic changes
Identify areas where the ecosystem needs adjustments from an economic point of view to maximize player engagement, retention, and revenue.
Collaborate closely with Product and Game Design teams to balance and design new features that address existing game shortcomings
Develop simulations and predictive models to actively anticipate the impact of logic changes for optimal player experience
Monitor individual and overall player balances to maintain the stability of the ecosystem of the economy
3+ years of experience working in the field of game economy
Strong understanding of numerical simulation methods and their applications (Monte Carlo, Metropolis-Hastings and so on)
Proven experience in economic modeling and quantitative analysis
Strong understanding of behavioral economics and motivational theories
Experience in predictive analytics, segmentation, and related areas
Ability to simplify and communicate complex economic concepts, influencing design decisions
Knowledge in SQL–an advantage
Intermediate Python or R–an advantage
State-of-the-Art Equipment: Doesn’t matter if you are a macbook or windows user, we will provide you with the technical gear you need to succeed
Engaging and diverse work environment: Join a diverse team, with over 19 nationalities and working from 13 different locations
Training & Development: Free language Courses with Chatterbug
Education allowance: Enjoy a personal development budget of up to 2000€/year for training, conferences, workshops etc.
Mental Health Support: Free personal coaching through our partner nilo.health to support our team members to live fulfilled lives at home and at work
Work-Life Balance and Flexibility: Flexible working hours and options for digital nomads, occasional office visitors, or regular office-goers
Germany-based benefits: 25 vacation days, free Gympass gold subscription, free monthly Deutschland-Ticket, and a monthly €50 tax-free internet contribution
Berlin Office Perks: Ergonomic setup, free lunch on a daily basis, and dog-friendly environment
* Benefits may vary depending on location and contract type. Do not hesitate to ask us about more details on our benefits offer.
A spirited, inspiring, international, and enthusiastic team,
An International team that is currently working from 13+ locations around the world,
An organization with a high level of trust and sense of belonging among employees, that prioritizes employee quality of life, job satisfaction and professional development,
An opportunity to be a part of a company that’s breaking with traditional ideas and taking a new approach that’s shattering how the games industry works.
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