Game Changing Data Scientist

Há 5 dias


Lisboa, Lisboa, Portugal Dmarket Tempo inteiro

Company Overview

DMarket, a subsidiary of Mythical Games, is a blockchain-enabled marketplace that allows for secure purchase and trade of virtual items. Our parent company, Mythical Games, is a leading game technology firm that powers the next generation of players, games, and studios. We are dedicated to launching exceptional video games that leverage distributed ledger tech and provide a platform for other game developers to do the same.

Salary and Benefits

The estimated salary for this position is between $120,000 - $180,000 per annum, depending on experience. In addition to a competitive salary, we offer a range of benefits including health insurance, retirement plans, and paid time off.

Job Description

We are seeking an experienced Data Scientist / Machine Learning Engineer to join our team in Europe. As a key member of our economics data science department, you will be responsible for designing, developing, and operating predictive models and algorithms that power business and retail user experience across our growing portfolio of digital game assets.

Required Skills and 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+

Responsibilities

  1. 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
  2. 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
  3. Assess, integrate, analyze, and build basic pipelines for new sources of internal and external data
  4. Collaborate with product managers and engineers to productize data solutions

Location

This role will be based in Europe and requires fluency in Ukrainian and English.



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