Data Engineer - Machine Learning & AI
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Hi, I'm Shubhang. I'm a Data Engineer at ZS Associates, where I've spent nearly three years building ML-driven analytics systems for healthcare clients — everything from segmentation models over 100K professionals to fault-tolerant ETL pipelines handling 500K+ records a month. And went out off the box, building APIs to power the dashboards and reduce the API response time to 60% and increase the UI experience by 15%.
I have owned and refactored the legacy pipeline, where I automated and optimised it to reduce the execution time from 3 days to 3 hours indicating a 96% of the improvement with higher accuracy results and cutting the manual intervention upto 25%. My work sits at the intersection of data engineering and machine learning — I've designed clustering and classification models over 100K+ data points, run A/B experiments to validate strategies before production, and reduced pipeline runtimes by 96% through cloud-native automation.
Built AI/ML-driven segmentation models (clustering & classification) on 100K+ healthcare professionals, improving targeting accuracy by 20% and reducing insight turnaround time by 30%.
Developed end-to-end AI analytics and data pipelines using Python, SQL, and PySpark, integrating predictive modeling, feature engineering, hypothesis testing, and A/B experimentation.
Engineered scalable ETL pipelines processing 500K+ records monthly, improving data freshness and AI/ML feature availability by 35%.
Implemented data validation, quality control, and enrichment frameworks, reducing manual data handling by 15% and ensuring high-quality AI/ML-ready datasets.
Refactored legacy workflows by automating orchestration and deploying cloud-based AI-ready data pipelines, reducing execution time by ~96% (3 days to 3 hours).
Optimized distributed Spark pipelines with schema validation, monitoring, and data quality layers, improving reliability and reducing manual intervention by 25%.
Designed and deployed 8+ RESTful APIs (Flask) to serve AI/ML datasets, reducing latency by 60% and enabling real-time analytics and dashboard integration.
Integrated AI/ML backend systems with visualization layers to enable dynamic dashboards and real-time insights, improving UX by 40%.
Collaborated with cross-functional teams to translate business requirements into AI-powered, production-ready analytics solutions, improving delivery velocity by 20%.
Delivered customer-facing AI/ML analytics solutions by gathering requirements and converting them into actionable BI dashboards for healthcare clients.
POSTGRADUATE DIPLOMA IN ADVANCE DATA SCIENCE in Data Science – IIIT BANGALORE | UPGRAD (2022-04 – 2023-07)
BACHELOR OF TECHNOLOGY in COMPUTER SCIENCE & ENGINEERING – MAHARAJA AGRASEN INSTITUTE OF TECHNOLOGY, ROHINI-22 (2019-08 – 2023-07)
