Shrunmay Shinde
Data Scientist @EllisDon
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WORK HISTORY
Data Scientist @EllisDon
Mississauga, ON, CA
Spearheading \"Vector-2\": Leading the development of a predictive risk engine on Google Cloud to provide early-warning signals for budget and schedule slippage.2. Large-Scale Portfolio Analysis: Scaling data solutions across a historical portfolio of 524 completed projects valued at $7.3B.3. BigQuery Engineering: Architecting robust SQL pipelines to process monthly records across 15+ complex relational databases.4. Stakeholder Collaboration: Conducting discovery interviews with Project Managers to translate operational friction into testable data metrics.5. Risk Modeling: Architecting multi-factor heuristic models assessing cost variance, safety, and delays to mathematically define \"risk\" in unlabeled datasets.
EDUCATION
University of Toronto - Rotman School of Management
Master of Management Analytics- MMA
Indian Institute of Information Technology, Pune
Bachelor of Technology - BTech, Computer Science
Rao Junior College of Science
Higher Secondary Education, Physics, Chemistry, Mathematics
ABOUT SHRUNMAY SHINDE
I am an Applied Data Scientist and Machine Learning Engineer who builds end-to-end AI systems—from raw data to production deployment.With a background in Computer Science (B.Tech) and Business Strategy (Rotman MMA), I don\'t just train models; I engineer them to solve real business problems at scale. I bridge the gap between research-grade algorithms and production-grade software.What I Bring:Machine Learning Engineering: Expertise in deploying Deep Learning models (Autoencoders, LSTMs) and building robust pipelines using Python, SQL, and Docker.Data Science & Analytics: Strong foundation in statistical analysis, A/B testing, and translating complex model outputs into actionable business strategies.Financial Focus: Specialized in Anomaly Detection, Fraud Prevention, and Credit Risk modeling for the Canadian banking sector.Technical Stack:Languages: Python, SQL, C++.ML & DL: PyTorch, TensorFlow, Scikit-learn, XGBoost, NetworkX (Graph).Deployment: Docker, Streamlit, Git, Cloud Basics (Azure/AWS).I am driven by the challenge of building \"Trustworthy AI\"—systems that are not only accurate but also explainable, compliant, and secure. Open to Data Scientist and ML Engineer roles starting in 2026.
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