ST Engineering

Overview of job

Role Purpose

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).

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.

• 14 days Annual leaves + 3 Sick leaves
• Private Health Insurance
• Annual Salary Review
• Performance Bonus
• 100% salary in probation period
• Free LinkedIn Learning Account
• Company Events & Team Building
• Opportunity to build the first AI Factory in finance across a global enterprise.
• Work on cutting-edge agentic AI and enterprise AI tools.
• Be part of a lean, high-impact team reporting to global finance leadership.
• Competitive package and growth path within a multinational group.

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).