Senior Specialist/Senior Specialist in Model Operations - Data Management Center

Purpose of the job title

The model operator will receive requests to deploy ML models from the Data Scientist team from the business units in the bank, convert the development code into operational code, and communicate with the Data Engineer/DevOps team to develop a data pipeline to plan the integration of ML models into the bank's operating system/application, and establish a mechanism to monitor and monitor the performance of ML models being operated.

Job description

• Implement ML models that are evaluated as effective Actual effectiveness on the operating environment as required by the business unit based on the development requirements document (BRD) (converting development code into operating code for the API development system or deploying the model on a dedicated platform such as IBM Cloud Paks for Data or coordinating with development units to directly integrate on the operating system/application at the bank)
• Coordinate with the Data Scientist team in the bank to plan to perform calibration and maintenance of the ML model in case the model performance falls below the allowable threshold
• Research, test, and gradually apply the CI/CD process and practice MLOps in the operation/development lifecycle of ML models (Continuous Delivery for Machine Learning - CD4ML) at the bank

a. Experience: 02 years or more of experience in the field of model operations (MLOps)

b. Professional requirements:

- Have experience/practice in one of the following areas:

+ Have experience using popular commercial platforms on the market to develop/operate ML models such as IBM Cloud Pak for Data, DataRobot, Alteryx, etc. or open source platforms such as Kubeflow, MLFlow, etc. Priority is given to candidates with practical experience on the IBM Cloud Pak for Data platform.

+ Proficient in using tools such as Hadoop, Spark, Airflow, Kafka to build data processing flows (data pipelines) to serve ML model operations.

+ Experience using Containerization tools (such as Docker), Software Orchestration (such as Kubernetes), and experience using CI/CD tools such as Jenkins, Gitlab.

- Priority is given to candidates with knowledge of popular libraries used in ML model development such as Keras, PyTorch, Tensorflow, Scikit-learn.

- Priority is given to candidates with experience working at financial institutions/banks/technology companies.

- Other skills/requirements:

+ Careful, meticulous, works well under pressure, and has good teamwork skills.

+ Ability to self-study/self-research well

Benefits

• Probation period 100% basic salary, total income 15-18 months/year
• High project bonus and year-end bonus
• Creative, modern working environment, management according to work progress and efficiency, flexible working hours
• Friendly, sociable leadership team, interested in individual development
• Employees are enthusiastically trained in soft skills and specialized expertise
• Fun atmosphere, young and dynamic colleagues
• Many interesting and meaningful collective activities: football, karaoke, backpacking, traveling, charity every year
• Maternity allowance for female employees
• Organize general health check-ups Annually, purchase additional health insurance packages for employees in addition to Medical Insurance