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Smruti Singh
Mid-level Implementation Engineer specializing in enterprise integrations and IAM/PAM
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About
Data/ML engineer with end-to-end ownership of donor-data deployments for a university foundation, delivering major performance and data-quality gains (500K+ records; 24h to 6h processing; duplicates 5% to 1%). Has put an LLM-assisted enrichment workflow into production with retrieval-grounded business rules, versioned outputs for traceability, and strong operational rigor around validation, logging, and CI/CD.
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Key Strengths
- Owned end-to-end customer deployment from discovery through post-launch stabilization
- Built parallelized Python data pipeline processing 500K+ records
- Reduced donor list generation time from ~24 hours to ~6 hours
- Improved data quality by reducing duplicate records from ~5% to ~1% via validation layers
- Bridged technical and non-technical stakeholders; communicated tradeoffs and progress
- Designed production workflow combining rule-based validation with LLM enrichment and retrieval grounding
- Implemented versioning/traceability for model outputs and pipeline results
- Debugged and remediated production integration incident (malformed JSON); added schema validation, logging, and CI/CD tests to prevent recurrence
- Designed robust ingestion patterns for messy inputs (normalization, controlled enrichment, fallback handling)
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