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Job Benefit

  • Insurance
  • Travel opportunities
  • Allowances
  • Incentive bonus
  • Health checkup
  • Training & Development
  • Salary review
  • Annual Leave

Job Description

 

1. Deploy and integrate AI/machine learning models

  • Develop and operate components within the MLOps platform.
  • Partner with data scientists to build and operate Feature Store.
  • Collaborate with relevant units to build/acquire new data sources for AI Center, EDA to facilitate developing new usecases.
  • Support the validation of machine learning models.
  • Design deployment architecture for machine learning model, leverage on premise and cloud based big data platforms to refactor and optimize code for production.
  • Automate data and machine learning engineering processes.
  • Monitor model quality post-deployment; support initiatives to improve model quality.

2. Conduct research and acquire new machine learning techniques

  • Conduct research on modern methods for AI/machine learning and engineering.
  • Proactively analyze and utilize existing/new data sources to support more impactful analyses.

3. Collaborate with business units on advanced analytics-related problems

  • Working with other centers/departments in EDA as well as Business Units to understand business problems to support them in better utilizing machine learning.
  • Support other centers/departments in providing prescriptive and predictive analyses when needed.

4. Training: Training other EDA team members on machine learning engineering.

Job Requirement

 

  • Bachelor’s degree in mathematics, Statistics, Engineering, Computer Science or other Quantitative discipline
  • Minimum 3-5 years of solid experience in data science, machine learning or big data engineering.
  • Proven experience in deploying AI/machine learning model to production.
  • Have knowledge and ability to work with cloud platforms.
  • Experience in data exploration/interpretation, working with statistical models, forecasting, machine learning algorithms, advanced analytical techniques.
  • Familiar with SQL and experience with data transformation.
  • Strong proficiency in at least one programming language Python/R.
  • Deep understanding of AI/machine learning, big data technologies (including Hadoop/Spark), distributed computing, software development and visualization. 

Hướng dẫn ứng tuyển

Bước 1: Điền vào Mẫu thông tin ứng viên VPBank, tải mẫu tại đây,
Bước 2: Chọn nút "Ứng tuyển" bên trên và làm theo hướng dẫn.
Bước 3: Sau khi hoàn tất bước ứng tuyển, nếu đã ứng tuyển thành công, Bạn sẽ nhận được Thư xác nhận ứng tuyển thành công từ VPBank. Vui lòng đọc email để nắm các thông tin hướng dẫn tuyển dụng tại VPBank. (Lưu ý: Ứng viên có thể Ứng tuyển bằng CV cá nhân)

Chúc Bạn Sức khỏe và Thành công.

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