Data Scientist (AI Factory Experience) - VCC

Key Responsibilities

• 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.

Candidate Profile

**Must-have**

• 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).