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Tier-1 employer and Gurgaon metro increase applicants, but senior niche ML/AI reduces density.
Requires deep financial domain, healthcare compliance, and enterprise LLM experience, limiting cross-industry fit.
Explicit 12+ years, domain-specific financial ML/LLM requirements, and enterprise production experience impose strict filters.
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Lead design and deployment of advanced ML models for financial forecasting and expense management.
Develop AI-driven business process optimization and reporting systems, including variance and scenario analysis frameworks.
Drive AI innovation, data governance, and mentor junior data scientists while collaborating with business leaders for actionable insights.
Minimum 12+ years experience in AI/Data Science with 8-10 years in financial domain AI/ML model development.
Proven track record in enterprise production-grade AI/ML projects for finance and experience with financial transactional datasets and ERP systems (SAP, Oracle, Workday).
Proficient in Python, advanced SQL, ML techniques, deep learning frameworks (TensorFlow/PyTorch), and enterprise Agentic AI solutions.
Bachelor's degree in Computer Science, Information Technology or related technical field.
Senior data science professional with strategic responsibility over end-to-end AI delivery lifecycle including multi-agent workflows and LLM integration.
Strong domain expertise in financial forecasting, variance analysis, and financial modeling with ability to translate complex ML outputs to non-technical stakeholders.
Experienced in stakeholder management at executive level to align technical innovation with measurable business ROI in healthcare/finance sectors.