The Role

• Development and support of services for generating responses and suggestions for support agents;

• Development and support of user fraud scoring services;

• Development of KYC mechanics using ML algorithms;

• Deployment and integrating ML models as services;

• Bringing best practices of working with the data in our DWH and Features store;

• Bringing best practices of working with MLOps infrastructure.

What we need

• 3+ years of experience as an ML Engineer or Data Scientist;

• Good knowledge of Python, understanding of best practices;

• Excellent knowledge of SQL, understanding of best practices;

• Classic DS & ML stack;

• Strong understanding of Applied Statistics and Statistical Analysis, understanding the principles of hypothesis testing;

• Proven record of improving business processes by integrating ML-based solutions end-to-end.