Zapraszamy do wysłania życiorysu - skontaktujemy się w przypadku wznowienia projektu lub podobnej oferty.
- Lead the design, analysis, and interpretation of data-oriented solutions to achieve business goals;
- Proactively perform data exploration to understand user behaviour and identify opportunities for improving our algorithms in the following areas: recommender systems, users live-time value prediction, fraud detection;
- Deal with both structured and unstructured data, collaborate with data engineers on defining data storage formats, data collection requirements;
- Set up reproducible experiments: selection, training, validation and optimisation of machine learning models, evaluation of their quality in business-related terms with split testing experiments;
- Be a part of the go-to-production team - create machine learning models, apply them to our data and support them in the productions;
- Good Python programming skills;
- Hands-on experience with Python data-related and ML-related libraries(pandas, numpy, sklearn and etc..);
- Hands-on experience with Python deep learning libraries (Tensorflow, Keras, PyTorch);
- Knowledge and understanding of classical machine learning (linear models, decision trees, ensembles for classification and regression tasks, clustering and dimensionality reduction);
- Knowledge and understanding of main concepts and stages of the modelling process (validation scheme, regularization, overfitting and generalization, data leaks, feature selection, etc.);
- Experience with relational databases and SQL, as well as with non-relational and NoSQL;
- Deep statistical skills utilized in A/B testing, analyzing observational data, and modeling;
- Ability to formulate data gathering requirements;
- Data visualization and presentation skills;
- Minimum 3-year experience in machine learning / data science;
- Work in an international IT product company with offices in 4 countries
- Remote full-time work or work from a comfortable office. It doesn't matter where you work from, what matters is the result
- Flexible schedule. It is enough to coordinate time zones and have intersections of working hours with the team
- Paid 4 sick days and 1 day off + 20 working days of vacation
- Sports program compensation
- Free online English lessons with a native speaker
- Large payments under the referral program, in which the bonus is received by both the employee who recommends and the candidate who accepts the offer
- Training, internal workshops, participation in international professional conferences and corporate events
- A wide relocation program for both employees and newcomers.
- Ability to implement space and time-efficient algorithms and understand which one is preferable and when;
- Familiarity with ClickHouse and MongoDB;
- Experience with distributed analytic processing technologies (Spark);
- Experience with Airflow;
- Experience with Docker, Kubernetes.
- Experience with AWS (SageMaker, S3, Lambda).