Data Scientist / Machine Learning Engineer

DMarket, recently acquired by Mythical Games, makes the secure purchase and trade of virtual items possible through our blockchain-enabled marketplace.

Mythical Games is a Venture-backed game technology company powering the next generation of players, games, and studios.  Our goal is to launch exceptional video games that leverage distributed ledger tech while also providing a platform that will allow other game developers to do the same.

At Mythical Games, we are proud of our ‘People First’ culture. We believe that it takes great people and culture to make great products.  By treating each other with empathy and respect, we can live fulfilling lives outside of our jobs while also creating exceptional work.

The Data Scientist / Machine Learning Engineer is at the forefront of leveraging data to shape the business’s strategic decisions and bring data-driven products to market. Reporting to the Head of Economics Data Science, this role will be primarily responsible for the design, development, and operation of predictive models and algorithms that power business and retail user experience across a growing portfolio of digital game assets. Our ideal candidate is someone who is passionate about data, and knows how to solve problems using a mix of economic theory, machine learning, and AI techniques, and industry experience in a financial or e-commerce setting.

The candidate will be based in Europe and will be required to communicate with colleagues in fluent Ukrainian and English.

Responsibilities:

• Develop, monitor, and improve the predictive models that power trading features on our marketplace; including random forest and neural net models for asset valuation, pricing, and fee optimization
• Develop and productize models that improve user interactions with our marketplace, for example, recommendation engines based on sparse matrix factorization, and customer churn / LTV prediction using reinforcement learning methods
• Assess, integrate, analyze, and build basic pipelines for new sources of internal and external data
• Collaborate with product managers and engineers to productize data solutions

Basic Qualifications

• Bachelor’s degree in a technical field with exceptional academic credentials (e.g., Mathematics, EE/CS, Statistics, or Operations Research)
• 3+ years of commercial experience as a Data Scientist, ML Engineer, or similar roles
• Proficiency in Python, including experience with scientific computing libraries such as NumPy, SciPy, pandas, and scikit-learn
• Proficiency with SQL
• Knowledge of statistics, econometrics, and machine learning
• English level Upper-intermediate+

Preferred Qualifications

• MA/MS. in a technical field such as Mathematics, Statistics, Economics/Finance, EE/CS, or Operations Research
• 2+ years’ experience working in a marketplace or e-commerce setting including as a contributor to strategic decisions
• Familiarity with the GCP suite, including BigQuery, and Cloud Functions
• Familiarity with Airflow workflow management tools
• Passion for video games

Location: Ukraine, Portugal.

We offer:

• Team of like-minded professionals who understand your game passion;
• Work in an international product company — Mythical Games is a resident of Diia City;
• Competitive financial reward;
• Health care starting on your first working day;
• 22 paid vacation days, paid sick leaves, and other personal days in accordance with the company’s internal policies;
• Flexible working hours;
• Referral bonuses;
• Financial support and PTO in case of special occasions are governed by the internal policies of the company.

Our team values diversity and believes that it strengthens our games, products, and communities.  We strongly encourage POC, folks with disabilities, those belonging to the LGBTQIA+ communities, and people across all gender to apply. 

If you need assistance with accommodations due to a disability, please reach out to accessibility@mythical.games.

We’ll be with you as soon as possible; our goal is to ensure an accessible and equitable interview process.