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Strong employer brand and metro location but senior specialized role limits applicant density.
Advanced analytics and prototyping skills transfer across industries, though marketplace domain experience increases specificity.
Explicit 8+ years plus deep SQL, prototyping, and LLM requirements create strict mandatory filters.
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Design and build AI-driven analytics prototypes using tools like Python, Streamlit, and SQL to demonstrate AI agents' data analysis and narrative generation capabilities.
Conduct deep business diagnostics on key performance metrics (e.g., GMV variances, funnel conversion) and translate manual analysis into structured logic and workflows for AI agents.
Collaborate with business leaders, data scientists, and AI developers to ensure AI outputs are accurate, verifiable, and actionable, facilitating the transition from prototypes to scalable production AI systems.
8+ years experience in advanced data analytics, business performance diagnostics, or data science.
Strong hands-on experience with building data prototypes and automated workflows using Python, Pandas, Streamlit, Gradio, or Jupyter Notebooks.
Deep expertise in SQL, data modeling, and complex business metric analysis including mix vs. rate impacts, A/B testing, and cohort analysis.
Familiarity with LLM/agent integrations and conceptual understanding of structured tool calls and retrieval-augmented generation.
Experienced in bridging complex business diagnostics with AI analytics product development, focusing on logic design and prototype validation.
Skilled in translating executive business questions into repeatable algorithms and detailed diagnostic blueprints for AI systems.
Comfortable working cross-functionally with both technical and business teams to ensure data accuracy, reproducibility, and explainability in AI-driven analytics.