AI Scientist

Job Overview And Responsibility

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. 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).