AI Factory Scientist

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, or

similar).

✓ Integrate AI solutions with enterprise platforms (ERP, BI tools, Dataiku, Google Vertex AI, Azure

OpenAI).

✓ 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).