Назад
Company hidden
1 месяц назад

Lead Data Scientist - Risk (Fintech)

Формат работы
onsite
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
Singapore
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
Для мэтча и отклика нужен Plus

Мэтч & Сопровод

Для мэтча с этой вакансией нужен Plus

Описание вакансии

Текст:
/

TL;DR

Lead Data Scientist (Fintech): Develop machine learning solutions for fraud detection with an accent on model creation, training, deployment, and production ML systems. Focus on debugging and troubleshooting ML systems, scaling integrations with software systems, and ensuring business impact through collaboration with stakeholders.

On-site in Singapore

Company

GoTo is the largest digital ecosystem in Indonesia, providing technology infrastructure for mobility, delivery, payments, financial services, e-commerce through Tokopedia, and banking via Bank Jago.

What you will do

  • Create, train, and deploy ML models for fraud detection.
  • Debug and troubleshoot production ML systems.
  • Collaborate with team members and stakeholders to deliver business impact.

Requirements

  • On-site in Singapore
  • Strong quantitative and problem-solving skills.
  • Solid understanding of Statistics/ML fundamentals and demonstrated Python experience.
  • Experience building and deploying deep neural network models in production.
  • Understanding of ML system design, scaling challenges, and integration with software systems.
  • Very good communication skills and ability to write clear technical documentation.
  • Ph.D. or Masters in quantitative discipline with 7+ years relevant experience.

Culture & Benefits

  • Part of GoTo Risk Data Science team in Common Capabilities.
  • Work in a leading Southeast Asian on-demand platform ecosystem.
  • Focus on empowering progress in the digital economy.

Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →