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Strong Tier-1 brand and senior ML title, but niche GenAI focus and seniority lower applicant density.
Role requires deep finance-domain knowledge plus GenAI expertise, limiting cross-industry transferability.
Mandatory 10+ years, finance domain experience, and specific GenAI/LLM toolset make filters very strict.
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Lead full lifecycle development of AI and ML models, including Agentic AI and Generative AI, to solve complex reconciliation and data engineering challenges at enterprise scale.
Drive measurable impact across Capital Markets operations, risk, and finance by deploying models in production and ensuring seamless integration and scalability.
Analyze large structured and unstructured financial data sets to identify trends and provide strategic recommendations to senior business and technology leaders.
10+ years of hands-on experience in Gen AI/ML development and big data engineering within Financial Services, Insurance, or Telecom sectors.
Expert-level proficiency in Python (including scikit-learn, TensorFlow, PyTorch, Pandas, NumPy) and SQL.
Proven experience building and deploying Agentic AI and LLM-based solutions using LangGraph, LangChain, and Agent Development Kit (ADK).
Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, Mathematics, Statistics, or related fields.
Demonstrates strong strategic capability in managing end-to-end AI/ML projects impacting global financial systems and reconciliation processes.
Experienced in collaborating with technical, operational, and business stakeholders to align AI/ML roadmaps with organizational goals and architecture standards.
Technically proficient in advanced supervised and unsupervised ML algorithms and enterprise-scale model deployment within regulated financial environments.