Data Scientist (Mandarin and English)

About the role

FPT Taiwan is building an AI‑Native Execution Hub and seeks a passionate Data Scientist fluent in Mandarin and English. You will turn data and research into intelligent, production‑ready solutions that power Acer’s AI ecosystem and serve global clients across manufacturing, supply chain, finance and operations.

Key responsibilities

• Develop and implement AI/ML models to solve real‑world challenges in manufacturing, supply chain, finance and operations.
• Collaborate with AI software engineers and product teams to translate research into deployable, maintainable services.
• Apply statistical, predictive and generative modeling to extract actionable insights from large‑scale structured and unstructured data.
• Design, automate and maintain end‑to‑end data pipelines ensuring data quality and workflow efficiency.
• Leverage Generative AI and LLM‑based architectures for intelligent automation and strategy generation.
• Monitor model performance, conduct retraining and validation using MLOps best practices.
• Contribute to AI optimization research and next‑generation AI‑driven decision systems.

Required profile

• Bachelor’s degree or higher in Computer Science, Mathematics, Statistics, Industrial Engineering, Financial Engineering or related AI/ML disciplines.
• 2+ years of practical experience in machine learning, deep learning, statistical modeling, optimization algorithms or numerical simulation applied to industrial or commercial problems.
• Experience with MLOps, ETL pipelines or data‑driven product development is a strong plus.
• Manufacturing domain knowledge, project management or software engineering experience preferred.
• Hands‑on experience with cloud platforms (AWS, Azure, GCP) or containerised environments (Docker, Kubernetes) advantageous.

Required skills

• Python programming
• Machine‑learning / deep‑learning frameworks: Scikit‑learn, PyTorch, TensorFlow, Keras, OpenCV
• Data preprocessing, feature engineering and exploratory data analysis
• Statistical inference and data visualization
• SQL and NoSQL databases
• Airflow for ETL pipelines
• Version control (Git, GitHub)
• CI/CD and DevOps workflows (Azure DevOps, GitLab CI)
• Cloud platforms (AWS, Azure, GCP)
• Containerisation (Docker, Kubernetes)