Parimatch Tech — hi-tech R&D center of the global holding company Parimatch. We are an innovative provider of future-defining tech solutions in the Gaming & Entertainment industry. We are committed to innovation to provide the global community with the highest quality products and gaming experience.
28 мая 2021

Middle Data Scientist for Risk Management Stream

Киев

Our product is a fraud-detection platform, specially designed for the betting business.

We started 2 years ago with a team created from scratch, dedicated processes and technology stack. Currently, we process, store and analyze over a billion events per day using ML and graph algorithms in real-time. We are going to reach two billion events during six to nine months adding more and more detailed data sources.

Unlike the majority of fraud-detection products available on the market, we are not wasting time on no-code/low-code and other marketing staff, focusing on our algorithms and business results instead.

As a part of the Data Science team of Risk Management Stream, you will work with challenging problems using a huge variety of data sources (bets, payments, site behavior data, etc.) detailed, enriched and collected for a long time.

You will have a direct impact on:

— Innovative solution for fraud detection;
— Real-time prediction;
— Data collection process;
— Strategic view and modelling roadmap.

Essential professional experience:

— Strong knowledge of Python (numpy, pandas, scikit-learn, etc.);
— Experience with big data technologies;
— Experience with at least one DL frameworks (Tensorflow, PyTorch);
— Experience in developing model from scratch (problem definition, data collection, feature engineering, model selection, validation, tuning, etc.);
— Deep understanding of classical ML Algorithms;
— Good knowledge of math and statistics;
— Good knowledge of PostgreSQL, MS SQL.

Desirable skills and personal features:

— Knowledge sharing abilities;
— High level of personal responsibility, readiness to commit on projects instead of tasks;
— Degree in Computer Science, Engineering, Mathematics or a related field.

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