Build and operate MLOps framework for developing and deploying data analytics models. Apply machine learning engineering approaches and best practices to package data analytic models for deployment, in the form of software applications or APIs to be used by consumers to run the models.
1. Develop KPI and see through its completion and enhance operational efficiency of MLE department.
Work directly with the Head of AI Center, Head of Data Science Office to give direction on the application of machine learning across the bank’s operations.
Working with other centers/departments in EDA as well as Business Units to understand business problems so as to support them in better utilizing machine learning.
Managing and directing a team of machine learning engineers in applying data science and engineering techniques in packaging data analytic models developed by Data Science Office.
Managing and directing a team of machine learning engineers in developing and operating the MLOps platform.
Partner with data scientists to build and operate Feature stores.
Collaborate with relevant units to pull new data sources for AI Center to facilitate developing new use-case.
Partner with data scientist to build criteria for validating machine learning model.
Develop 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 performance, business impact after deployment; support retrain to improve model quality.
Coach & train team members.
2. Conduct research and acquire new machine learning techniques
Conduct research on modern methods for machine learning and engineering.
Proactively analyze and utilize existing/new data sources to support more impactful analyses
3. Partner business units on advanced analytics-related problems
Working with other centers/departments in EDA as well as Business Units to understand business problems so as to support them in better utilizing machine learning
Training other EDA team members on machine learning
Job Requirement
Job requirements:
Bachelor degree in Mathematics, Statistics, Engineering, Computer Science or other Quantitative discipline
Min 7 years of solid experience in data science, machine learning or big data engineering.
Min 3 years of experience in a management position
Experience in building a new team from scratch is a plus
Experience in interpreting data and translate them into actionable insights, not just data extraction and reporting
Experience in working with cloud environment
Deep knowledge and experience working with statistical models, forecasting, machine learning algorithms, and advanced analytics techniques
Experience in working with SQL and Excel
Proficiency in at least one programming language R/Python
Advanced knowledge in big data and machine learning tech stack including Hadoop and Spark.
Proficiency in big data technologies, distributed computing, software and visualization development
What we offer:
Attractive income, competitive salary and bonus according to ability (16-18 month package)
Bonus on Holidays and New Year (according to banking policy from time to time)
Get preferential loans according to the bank's policy from time to time
Attractive leave mode according to job rank (16-18 paid leaves/year)
Compulsory insurance according to labor law & VPBank care insurance for employees depending on rank and working time
Participate in training courses depending on the Training Framework for each position
Dynamic, friendly working environment with many opportunities for training, learning and development; participate in many interesting cultural activities (sports event, talents, teambuilding activities...)
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