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10 дней назад

Senior Data Scientist (Machine Learning)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
c1
Страна
Indonesia
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Senior Data Scientist (Machine Learning) (Credit Risk and Predictive Modeling): Building and improving end-to-end machine learning models for credit risk and growth applications with an accent on quantitative analysis, robust predictive modeling, and large-scale data. Focus on researching new modeling approaches, developing credit risk models, and translating discoveries into production-ready products.

Location: Jakarta, Indonesia

Company

hirify.global develops financial technology products using data science and machine learning.

What you will do

  • Turn data science discoveries and ideas into machine learning models and final products.
  • Prototype models for credit risk and growth-related applications.
  • Research ways to improve models using large and diverse datasets.
  • Build robust end-to-end predictive models with modern machine learning techniques.
  • Collaborate with analysts and machine learning engineers across multiple countries.
  • Contribute to advancing data science capabilities at hirify.global.

Requirements

  • More than 5 years of relevant work experience.
  • Deep expertise in credit risk and 3–4 years of experience building credit risk models.
  • Master's degree, PhD, or equivalent experience in a quantitative field such as computer science, mathematics, statistics, econometrics, engineering, or artificial intelligence.
  • Strong statistics and mathematics skills, with independent working and communication abilities.
  • Proficiency in Python or R and experience with RDBMS and NoSQL platforms, including MySQL, PostgreSQL, and S3.
  • Excellent English communication skills.

Nice to have

  • Experience using alternative data to evaluate credit risk.
  • Experience building end-to-end deep learning or NLP models.
  • Experience working in a financial institution.

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