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Shuvam Mitra
Mid-level Data Scientist specializing in anomaly detection and production ML
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About
Interned at Backblaze building production AI systems for incident response and security operations, including an internal LLM-powered incident triage assistant that used Snowflake + RAG over historical tickets/postmortems and delivered results via Slack and a web UI. Emphasizes reliability (PII filtering, grounding, schema validation, fallbacks) and rigorous evaluation/observability (offline replay, partial rollouts, time-to-first-action metrics, Prometheus/Grafana).
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Key Strengths
- Built and deployed a production LLM incident triage assistant (RAG + strict JSON outputs) for on-call engineers
- Strong focus on reliability: PII-aware log cleaning, hallucination reduction via retrieval grounding, schema validation, and graceful fallbacks
- Data-driven iteration using engineer feedback loops to refine prompts and retrieval filters
- Practical evaluation mindset: offline replay evals + online partial rollouts with instrumentation and A/B comparisons
- Pipeline engineering and observability: modular DAG/task design, structured logging with correlation IDs, and metrics dashboards (Prometheus/Grafana)
- Effective cross-functional delivery with non-technical security stakeholders; translated goals into measurable signals and reduced false positives
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1 publication
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