Если вы раньше входили через Google, сбросьте пароль для своей Gmail-почты через кнопку «Забыли пароль?» на экране входа. Затем войдите по email и новому паролю.
Если аккаунта ещё нет, зарегистрируйтесь с Gmail-почтой, после подтверждения почты мы предложим задать пароль.
Что нового
Загружаю обновления...
Что нового
Загружаю обновления...
Работа найдется быстрее с подпискойКандидат найдётся быстрее с подпиской
Чтобы адаптировать резюме под вакансию или составить сопроводительное письмо, загрузите резюме
описание
Wise is a global technology company building a way to move and manage money worldwide. It helps people and businesses send money internationally, spend abroad, and make and receive international payments.
задачи
Participate in planning and ideation of data science projects with cross-functional teams;
Identify opportunities to apply machine learning and data science techniques;
Explain the value, limitations, and potential impact of data science initiatives to stakeholders with different levels of understanding;
Manage and create large image and tabular datasets related to KYC processes;
Iterate on deep learning image models;
Measure and optimise machine learning model performance;
Maintain and develop a large Python codebase using industry-standard best practices;
Monitor developments in machine learning and research how to incorporate new ideas into production systems;
Research document verification to identify effective ways to prevent criminal activity;
Mentor junior team members and support their growth in data science skills and adherence to industry standards.
требования
Experience applying machine learning and data science techniques;
Experience with machine learning model training, testing, lifecycle management, and performance analysis;
Experience working with deep learning image models;
Experience managing large image and tabular datasets;
Strong Python development skills;
Ability to articulate data science concepts, value, limitations, and impact to diverse stakeholders;
Ability to research and incorporate new machine learning approaches into production systems;