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Tier-1 employer, metro location, and broadly recognizable Data Scientist manager title increase candidate competition.
Specialized financial and healthcare ML/LLM requirements make cross-industry transferability limited.
12+ years, domain-specific ML/LLM experience and enterprise production requirements create highly stringent filters.
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Lead advanced analytics and AI initiatives to optimize financial forecasting and budget planning across the organization.
Design, develop, and deploy production-grade machine learning and Agentic AI models for key financial KPIs and process optimization.
Own end-to-end AI project lifecycle including technology selection, governance, risk mitigation, and stakeholder management with measurable ROI impact.
12+ years of experience in AI/Data Science with 8-10 years focused on AI/ML in the financial domain.
Proven experience delivering enterprise-level production AI/ML solutions for financial forecasting using large financial datasets and ERP systems (SAP, Oracle, Workday).
Strong proficiency in Python, SQL, ML methods, deep learning frameworks, data visualization tools, and cloud platforms (AWS/Azure/GCP/OCI).
Bachelor's degree in Computer Science, Information Technology, or related technical field.
Demonstrated ability to lead strategic AI delivery within complex enterprise financial environments and cross-functional teams.
Experienced in implementing cutting-edge Agentic AI and LLM-based solutions with responsibility for AI tech stack governance and mitigation of model risks.
Skilled in translating complex AI/ML insights into actionable financial strategies for senior leadership and diverse stakeholders.