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Metro location and mid-level seniority increase competition, but niche Generative AI skillset reduces applicant pool.
Capital Markets domain knowledge and specialized Generative AI skills limit cross-industry transferability.
Explicit 6+ years plus mandatory Generative AI, Databricks, Azure and domain expertise enforces strict filters.
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Lead design, development, and deployment of machine learning models for forecasting, classification, and anomaly/fraud detection in Capital Markets.
Architect and implement Generative AI solutions including RAG pipelines, prompt engineering, vector databases, and agent-based AI systems on cloud platforms (Azure preferred).
Develop and maintain modular, production-ready Python AI applications following SOLID principles, and implement MLOps practices for model deployment, monitoring, and optimization.
6+ years of experience in Data Science, Machine Learning, or AI-related roles.
Bachelor’s degree is mandatory.
Proficiency in Python and SQL, with strong software engineering skills including SOLID design principles.
Experience with Generative AI technologies (LLMs, RAG, prompt engineering) and cloud platforms (Azure preferred) specifically applied to Capital Markets or fraud detection use cases.
Experienced in end-to-end AI/ML model lifecycle management including deployment and monitoring using MLOps.
Demonstrated expertise in Generative AI frameworks like LangChain, LangGraph, CrewAI, or AutoGen, capable of building scalable LLM-based solutions.
Strong domain knowledge of Capital Markets and fraud detection to translate complex data into actionable business insights effectively.