{"id":2580683,"url":"https://alion.io/job/newbridge-alliance-data-scientist","title":"Data Scientist","company":{"id":4423579,"name":"Newbridge Alliance Pte","domain":"newbridgealliance.com","url":"https://alion.io/company/newbridgealliance","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chongqing, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":63000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":865},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CrewAI","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"n8n","optional":false},{"name":"OpenAI","optional":false},{"name":"Power Automate","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"UiPath","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-15T01:52:06Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T10:30:09Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"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.\nKey Responsibilities\nBuild and deploy AI/ML pipelines to automate core finance processes such as closing, reconciliations, forecasting, and tax analytics\nDevelop agentic AI systems using multi-agent frameworks (CrewAI, AutoGen, LangGraph, or equivalents)\nIntegrate AI solutions with enterprise platforms like ERP systems, BI tools, Dataiku, Google Vertex AI, and Azure OpenAI\nCreate supervised and unsupervised ML models for forecasting, anomaly detection, and fraud/risk analysis\nFine-tune large language models on finance data while adhering to compliance and governance standards\nSet up monitoring, retraining, and performance management for deployed models\nConvert finance workflows into AI use cases with measurable ROI (e.g., >20% time reduction, >30% accuracy improvement)\nDeliver pilot projects within 90 days and scale them enterprise-wide within 6-12 months\nPartner with process owners to drive adoption and maintain governance\nEnsure solutions meet audit, data privacy, and regulatory requirements\nIncorporate explainability and traceability into all production models\nCandidate Profile\n4-7 years in data science or ML engineering with production-grade deployments\nExperience with AI factory approaches-modular design, reusable components, orchestration frameworks\nProficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow), SQL, and APIs\nHands-on work with agentic AI frameworks such as CrewAI, AutoGen, LangChain, or LangGraph\nCloud deployment experience on Google Vertex AI, Azure ML, AWS SageMaker, or similar\nProven record of delivering productivity projects with measurable ROI\nFamiliarity with finance/accounting processes (forecasting, close, compliance, treasury)\nKnowledge of Dataiku DSS or comparable low-code AI platforms\nExperience with workflow automation tools (Power Automate, UiPath, n8n)\nPrior experience in a shared-services or multinational finance environment\nBilingual in Vietnamese and English\nSuccess Metrics (First 12 Months)\nLaunch at least 3 AI pilots in FP&A/Accounting achieving >20% productivity gains\nCreate reusable AI components for the finance AI Factory (agents, connectors, templates)\nDeliver >US$500k in cost savings through AI-enabled automation\nPut in place a governance framework for finance AI covering accuracy, auditability, and risk\nWhy Join\nChance to build the first finance AI Factory for a global enterprise\nWork on cutting-edge agentic AI and enterprise AI technologies\nBe part of a lean, high-impact team reporting directly to global finance leadership\nCompetitive compensation with a clear growth path in a multinational 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