Data Scientist

🏢 Newbridge · all Newbridge jobs
📍 China
📅 Posted 2026-08-17 · via Himalayas
🏷 Data-Science,Machine-Learning-Engineering,AI-Engineering,AI-ML-Specialist,Data-Scientist,Search-Data-Scientist,AI-Data-Scientist,Data-Science-Expert,Data-Science-Specialist,ML-Data-Scientist,Fintech,Data-Scientist---Analytics
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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. You'll work with FP&A, Accounting, Tax, Treasury, and IT to take AI solutions from prototype to full-scale production, targeting clear business impact—time 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 6–12 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 - 4–7 years in data science or ML engineering with production-grade deployments - Experience with AI factory approaches—modular 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 Originally posted on Himalayas

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