HBLAB Việt Nam 3.3 ★

Model Development: Design and develop machine learning models to solve complex financial problems, including risk assessment, fraud detection, and predictive analytics.
Data Analysis: Collect, preprocess, and analyze large datasets from various financial sources to extract meaningful insights.
Algorithm Implementation: Implement and optimize machine learning algorithms and techniques to improve model accuracy and performance.
Collaboration: Work closely with data scientists, software engineers, and financial analysts to integrate machine learning models into the platform.
Performance Monitoring: Monitor and evaluate the performance of deployed models and make necessary improvements.
Documentation: Create comprehensive documentation for developed models and algorithms, including technical specifications and user guides.Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
Experience:
5 years' experience as a Machine Learning Engineer or Data Scientist.
Experience in the financial industry, working on financial models, risk assessment, or related areas.
Technical Skills:
Proficiency in programming languages such as Python, R, or Java. o Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience with data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure)Salary shall be discussed during the interview;
Monthly working allowance when working at client's office;
5 working days per week (Monday-Friday), some extent flexible working hours;
Friendly, professional and open working environment;
Premium Heath Care Insurance 24/7 for Key Person;
Company Trip and Events, Birthday Party, Year End Party;
Labor Contract, Social insurance as Labor Law;
Training courses: Technical skills, Japanese;
Professional and Flexible Working Environment.