Responsibilities
We are building an AI Factory to transform finance and accounting across Asia, the US, and Europe. This role is critical in designing, developing, and deploying AI-driven automation, ML models, and agentic AI workflows that improve productivity, accuracy, and insight generation for a 600-person finance organization.
The Data Scientist will partner with FP&A, Accounting, Tax, Treasury, and IT teams to industrialize AI solutions — from prototype to scaled production — with a focus on measurable business outcomes (time savings, error reduction, working capital impact, forecast accuracy).
✓ Design and deploy AI/ML pipelines to automate finance processes (close, reconciliation,forecasting, tax analytics).✓ Develop agentic AI systems (multi-agent workflows with CrewAI, AutoGen, LangGraph, orsimilar).
✓ Integrate AI solutions with enterprise platforms (ERP, BI tools, Dataiku, Google Vertex AI, AzureOpenAI).
✓ Build supervised/unsupervised ML models (forecasting, anomaly detection, fraud/risk analysis).
✓ Fine-tune LLMs on finance datasets with strict compliance and governance controls.
✓ Implement monitoring, retraining, and performance management frameworks for models.
✓ Translate finance workflows into measurable AI use-cases with ROI (e.g., >20% time savings,>30% accuracy uplift).
✓ Deliver pilots in <90 days and scale to enterprise level within 6–12 months.
✓ Work closely with process owners to ensure adoption and governance.
✓ Ensure AI solutions meet audit, data privacy, and regulatory requirements.
✓ Build explainability and traceability into deployed models
Requirements
✓ 4–7 years in data science / ML engineering with proven production deployments.✓ Hands-on experience with AI factory models: modular design, reusable components,orchestration frameworks.
✓ Proficient in Python (pandas, scikit-learn, PyTorch/TensorFlow), SQL, APIs.
✓ Experience with agentic AI frameworks: CrewAI, AutoGen, LangChain, LangGraph, or similar.
✓ Cloud deployment skills: Google Vertex AI, Azure ML, AWS Sagemaker, or equivalent.
✓ Strong track record in delivering business productivity projects with measurable ROI.
Nice to have:
✓ Exposure to finance/accounting processes (forecasting, close, compliance, treasury).
✓ Familiarity with Dataiku DSS or similar low-code AI factory platforms.
✓ Experience with workflow automation (Power Automate, UiPath, n8n).
✓ Previous work in a shared services or multinational finance organization.
✓ Bilingual (Vietnamese + English).Key Metrics of Success (First 12 Months)
✓ Deliver ≥3 AI pilots in FP&A/Accounting with >20% productivity gain.
✓ Build reusable AI components for the finance AI Factory (agents, connectors, templates).
✓ Demonstrate cost savings of >US$500k equivalent through AI-enabled automation.
✓ Establish governance framework for AI in Finance (accuracy, audit, risk).