I turn messy, multi-source data into decisions that move the needle — building ML models, BI dashboards, and analytics pipelines for healthcare and finance.
I'm a Data Analyst & ML Engineer based in Boston, with 3+ years of turning complex, multi-source data into business-ready insights and predictive models.
Currently at CSG International, I work across healthcare and fraud analytics — designing ETL pipelines, deploying Power BI dashboards, and supporting predictive risk-scoring models that have driven real business outcomes.
Before that, I automated KPI/SLA reporting at Ciena using Alteryx and Python — saving the team ~$250K annually.
I just finished my MS in Data Analytics Engineering at Northeastern University, where I worked on ML projects spanning medical imaging, recommendation systems, and full-stack web platforms.
Healthcare, fraud, telecom — end-to-end analytics across regulated industries.
Real problems across ML, analytics, and full-stack systems — built end-to-end.
CNN-based multi-class classification pipeline for brain tumor detection from MRI scans. Implemented and compared deep learning architectures (ResNet, VGG) to optimize precision and recall across 4 tumor categories.
Analyzed 50K+ patient records using SQL and Python to identify key drivers of 30-day hospital readmissions. Cohort and trend analysis surfaced patterns contributing to ~25% of readmissions, directly informing clinical intervention strategies.
EDA on 500K+ transaction records to surface fraud patterns using optimized SQL queries (joins, CTEs, window functions). Built dynamic Power BI and Tableau dashboards monitoring fraud rate, transaction trends, and risk segmentation — cutting manual review by 40%.
Power BI dashboards analyzing revenue performance across 15+ regions with DAX measures and calculated columns. Time-series analysis surfaced seasonal patterns and growth opportunities — automated recurring reporting, reducing manual effort by 50%.
Recommendation engine combining collaborative filtering and content-based approaches. Built NLP pipeline for sentiment analysis on user reviews to generate features for personalized restaurant ranking across 10K+ reviews.
End-to-end system for managing academic reports and student records with role-based access control, automated report generation, and administrative workflow management.
Full-featured e-commerce web portal with product catalog, shopping cart, order management, and customer authentication. Implemented responsive design and database-backed inventory management.
Currently seeking Data Analyst and ML Engineer roles in Boston or remote. Let's talk about how I can drive results on your team.
y.lokesh.chowdhary@gmail.com