City of Rochester

In partnership with the City of Rochester and Simon Vision Consulting, I spearheaded a project to streamline their workers’ compensation process for employees in refuse collection and street maintenance. As a consultant, I examined over 500 injury claims to uncover key trends, leading to a 30% reduction in reported injury rates.

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I developed an end-to-end, data-driven approach—focusing on data preprocessing, feature engineering, and imputation—to prepare over 200,000 records for analysis. Leveraging advanced unsupervised models like Isolation Forest and One-Class SVM, I designed an anomaly detection pipeline that identified 5% of data points as potential fraud indicators.

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Driving ML-based process automation with models such as XGBoost and Isolation Forest, I boosted workflow efficiency by 25%, reduced high-risk claims by 13%, and cut processing errors by 15%. By gathering stakeholder feedback and presenting data-driven recommendations to city officials, our work ultimately improved claims processing efficiency by 25%, paving the way for smarter, more strategic decision-making.

Recommendation from the Project Manager

Angela Bansal
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"Shivam was an invaluable asset to my team for a Simon Vision Consulting project. His leadership skills were exceptional, and he consistently boosted the morale of his teammates with his positive attitude and support. Shivam showed remarkable dedication, passion, and integrity in his work, always striving for excellence. He confidently presented in front of the client and took the lead with ease, showcasing his strong communication and management abilities. He is a wonderful team player, and it was a pleasure working with him. I am confident he will excel in any opportunity he pursues."

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