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Hemant Deshmukh
Mid-level Data Engineer specializing in cloud data pipelines and analytics engineering
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About
Built and deployed a production LLM-powered demand and churn forecasting system for an e-commerce client, combining open-source LLMs (LLaMA/Mistral) and Sentence-BERT embeddings to generate business-friendly explanations of forecast drivers. Strong focus on data quality and model trust (validation, baselines, segmented monitoring) and production reliability via Airflow-orchestrated pipelines with readiness checks, retries, and ongoing drift/A-B testing.
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Key Strengths
- Built and deployed production LLM-powered demand/churn forecasting for e-commerce pricing and inventory decisions
- Strong data quality discipline (missing/duplicate/outlier/unit checks; separating promo spikes from true demand)
- Improves model trust via baseline comparisons, segmented performance tracking (product/channel), and stakeholder reviews
- Production-grade orchestration with Airflow (dependencies, retries, alerts) and resilient handling of late/partial upstream data
- Rigorous AI workflow evaluation (gold datasets, unit/integration/E2E tests, A/B testing, drift monitoring, versioning)
- Effective translation of model outputs into human-readable explanations for non-technical auditors/planners
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