Data Scientist

Chongqing - China

Monthly Salary: Not Disclosed

Posted on: 14 hours ago

Vacancies: 1 Vacancy

Job Summary

Our client is creating an AI Factory to modernize finance and accounting across Asia the US and Europe. This role is central to designing building and rolling out AI-driven automation machine-learning models and agentic AI workflows that boost productivity accuracy and insight for a 600-person finance team. Youll work with FP&A Accounting Tax Treasury and IT to take AI solutions from prototype to full-scale production targeting clear business impacttime savings fewer errors better working capital and improved forecast accuracy.

Key Responsibilities

Build and deploy AI/ML pipelines to automate core finance processes such as closing reconciliations forecasting and tax analytics
Develop agentic AI systems using multi-agent frameworks (CrewAI AutoGen LangGraph or equivalents)
Integrate AI solutions with enterprise platforms like ERP systems BI tools Dataiku Google Vertex AI and Azure OpenAI
Create supervised and unsupervised ML models for forecasting anomaly detection and fraud/risk analysis
Fine-tune large language models on finance data while adhering to compliance and governance standards
Set up monitoring retraining and performance management for deployed models
Convert finance workflows into AI use cases with measurable ROI (e.g. >20% time reduction >30% accuracy improvement)
Deliver pilot projects within 90 days and scale them enterprise-wide within 612 months
Partner with process owners to drive adoption and maintain governance
Ensure solutions meet audit data privacy and regulatory requirements
Incorporate explainability and traceability into all production models

Candidate Profile

47 years in data science or ML engineering with production-grade deployments
Experience with AI factory approachesmodular 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

Success Metrics (First 12 Months)

Launch at least 3 AI pilots in FP&A/Accounting achieving >20% productivity gains
Create reusable AI components for the finance AI Factory (agents connectors templates)
Deliver >US$500k in cost savings through AI-enabled automation
Put in place a governance framework for finance AI covering accuracy auditability and risk

Why Join

Chance to build the first finance AI Factory for a global enterprise
Work on cutting-edge agentic AI and enterprise AI technologies
Be part of a lean high-impact team reporting directly to global finance leadership
Competitive compensation with a clear growth path in a multinational group

Key Responsibilities

Build and deploy AI/ML pipelines to automate core finance processes such as closing reconciliations forecasting and tax analytics
Develop agentic AI systems using multi-agent frameworks (CrewAI AutoGen LangGraph or equivalents)
Integrate AI solutions with enterprise platforms like ERP systems BI tools Dataiku Google Vertex AI and Azure OpenAI
Create supervised and unsupervised ML models for forecasting anomaly detection and fraud/risk analysis
Fine-tune large language models on finance data while adhering to compliance and governance standards
Set up monitoring retraining and performance management for deployed models
Convert finance workflows into AI use cases with measurable ROI (e.g. >20% time reduction >30% accuracy improvement)
Deliver pilot projects within 90 days and scale them enterprise-wide within 612 months
Partner with process owners to drive adoption and maintain governance
Ensure solutions meet audit data privacy and regulatory requirements
Incorporate explainability and traceability into all production models

Candidate Profile

47 years in data science or ML engineering with production-grade deployments
Experience with AI factory approachesmodular 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

Success Metrics (First 12 Months)

Launch at least 3 AI pilots in FP&A/Accounting achieving >20% productivity gains
Create reusable AI components for the finance AI Factory (agents connectors templates)
Deliver >US$500k in cost savings through AI-enabled automation
Put in place a governance framework for finance AI covering accuracy auditability and risk

Why Join

Chance to build the first finance AI Factory for a global enterprise
Work on cutting-edge agentic AI and enterprise AI technologies
Be part of a lean high-impact team reporting directly to global finance leadership
Competitive compensation with a clear growth path in a multinational group