Data Scientist

We are searching for a passionate Data Scientist to help with our Machine Learning tasks and statistical analysis. Please note that we work in hybrid model, 3 days in the office and 2 days remotely.

• Work with business and technical stakeholders to choose the most appropriate Machine Learning solutions.
• Design and develop ML models for use-cases like: recommender systems fraud detection chat text analysis.
• Work with data engineers to select appropriate datasets and data representation methods.
• Work with game developers to make sure that the necessary data are available.
• Research and implement appropriate ML algorithms and tools.
• Devise metrics and evaluation processes for the performance and impact of your models.
• Train, test and retrain ML models.
• Work with other team members to deploy ML models to production.
• Use and, where necessary, extend existing ML libraries and frameworks.

• University degree in numerical field (Machine Learning, Statistics, Mathematics, Computer Science, Physics, Engineering, etc.) (required)
• Proven track record and excellent ability to understand, interpret and explain business data (required)
• At least 3 years of work experience in the Data Science field (required)
• Experience and understanding of linear algebra and statistical modelling (required)
• Experience with deploying ML solutions to production (required)
• In-depth knowledge in at least one ML field such as regression, classification, clustering, pattern mining or optimization (required)
• Experience with at least one ML framework such as Scikit-Learn, Keras, Tensorflow, Pytorch, MLLib (required)
• Hands-on with Python, in particular packages such as Pandas, Numpy, Matplotlib (or equivalent) (required)
• Experience with SQL and Big data tools such as Spark/Hive (required)
• Highly proficient in spoken and written English (required)
• Excellent communication skills and a pragmatic approach to problem solving (required)
• Willingness to learn and interest in latest trends in programming and ML (required)
• Knowledge of Scala or Java (nice-to-have)
• Experience with AWS or other cloud provider (nice-to-have)
• Experience with Kafka, Clickhouse, Postgres, Kubernetes, Docker (nice-to-have)

• Opportunity to influence the quality of the products, improve process and implement your ideas
• Social package, including sport compensation & medical insurance
• Professional growth
• Sport activities, parties, team buildings