Data Scientist

Build and deploy AI/ML pipelines to automate core finance processes such as closing, reconciliations, forecasting, and tax analytics. Develop agentic AI systems and integrate AI solutions with enterprise platforms. Create supervised and unsupervised ML models for forecasting, anomaly detection, and fraud/risk analysis.

Requirements

• 4-7 years in data science or ML engineering with production-grade deployments
• Experience with AI factory approaches—modular design, reusable components, orchestration frameworks
• Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow), SQL, and APIs
• Hands-on work with agentic AI frameworks such as CrewAI, AutoGen, LangChain, or LangGraph
• Cloud deployment experience on Google Vertex AI, Azure ML, AWS SageMaker, or similar
• Proven record of delivering productivity projects with measurable ROI
• Familiarity with finance/accounting processes (forecasting, close, compliance, treasury)
• Knowledge of Dataiku DSS or comparable low-code AI platforms
• Experience with workflow automation tools (Power Automate, UiPath, n8n)
• Prior experience in a shared-services or multinational finance environment
• Bilingual in Vietnamese and English

Benefits

• Competitive compensation
• Clear growth path in a multinational group

Tagged as: Data Analysis, Financial Modeling