N
Nishith Gajjala
About
Detail
United States
Résumé
Jobs
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AI / ML EngineerDiscoverJul 2025 - Current (1 year 4 months)• Led the end-to-end migration of enterprise data from AWS and GCP into a unified Azure Data Lake, creating a single source of truth for AI models across 3 business units.
• Designed and owned the entire data ingestion module using Python and Dataflow, enabling both batch processing and real-time API-based predictions for NLP models.
• Productionized ML and NLP models using Docker and Kubeflow, implementing automated CI/CD pipelines that reduced deployment failures by 25%.
• Built cloud access control and infrastructure provisioning from scratch using IAM and Terraform, cutting cloud costs by 18% through optimized resource tagging.
• Architected optimized data schemas and consumption layers with SQL and Hadoop, reducing- AI / Data AnalystCVS HealthJun 2023 - Jun 2024 (1 year 1 month)• Led the data modeling module for the Health System covering Pharmacy, Claims, and Patient History, working directly with Product Managers to finalize schema sign-offs.
• Analyzed complex healthcare claims data using SQL and data validation techniques, delivering insights that reduced clinical reporting errors by 20%.
• Partnered with database architects to design logical and physical data models, ensuring referential integrity and optimized indexing for 10M+ patient records.
• Developed and maintained T-SQL database objects (stored procedures, views, triggers, materialized views), improving data retrieval speed by 30%.
• Performed source-to-target data profiling and mapping using SSMS, ensuring 100% consistency during - MData ProfessionalMacy’sJan 2020 - Nov 2022 (2 years 11 months)• Led the end-to-end development of a predictive inventory optimization module using machine learning, improving business outcomes by 18%.
• Analyzed structured and unstructured sales data using Python and statistical techniques, identifying 3 high-impact features that reduced stockouts by 12%.
• Developed and deployed supervised learning models (random forest, XGBoost) to optimize supply chain processes, reducing operational risks by 15%.
• Owned the feature engineering pipeline for 50+ variables, including lag features and rolling windows, increasing model F1-score from 0.72 to 0.84.
• Collaborated with engineering and product teams through requirement-gathering sessions, translating business needs into scalable Python
Education
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- CBachelors in Electronics & Communication EngineeringCMR Technical Campus, India
- SMaster of Science in Computer and Information SciencesSouthern New Hampshire University, USA