— Own, build and continuously improve data infrastructure. Become an expert on all aspects of data science, machine learning and analytical infrastructure;

— Own, build and manage scalable batch/real time pipelines for ingesting, processing, and delivering data to our business users;

— Understanding full lifecycle Machine Learning solutions;

— Apply quality measures to ensure data governance, accuracy, quality and integrity;

— Help drive engineering-wide initiatives with other engineering leaders;

— Contribute to influence the ML infrastructure roadmap based on the feedback from customers;

— Act as a bridge between the business and technical stakeholders in the development of new ML models and data solutions;

— Identify new opportunities to leverage data science to different parts of the various Yalantis projects;

— Research, patterns identification and formulating insights;

— Build the ML infrastructure and platform to accelerate and make its development accessible and efficient to all engineers.

Чем Вы должны обладать

Обязательно

— Hands on experience with DS/ML concepts: regression and classification, clustering, feature selection, feature engineering, curse of dimensionality, bias-variance tradeoff, neural networks, SVMs, etc.;

— Experience working in Linux and Docker environment;

— Experience with AWS and AWS Machine Learning services (such as AWS Personalise, SageMaker etc) or Google and GC Machine Learning services;

— Good knowledge of the Python programming language;

— Experience translating a high-level strategy and roadmap into an execution plan will be a big advantage;

— Can effectively set and communicate priorities for self tasks and needs;

— Experience working on financial models or banking products;

— Holds a master’s degree in computer science, engineering, or math;

— Upper-intermediate English level;

Что Вы получаете Предлагаем

— Great compensation and social packages;

— Medical insurance;

— Sport and education compensation;