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shreya vare

@shreyavare

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Machine learning and data science intern focused on fast, accurate predictive models and actionable insights.

India

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What I'm looking for

I’m eager to contribute to machine learning and data science work—building predictive models, applying NLP for insights, and presenting results through dashboards—while learning from a team that values experimentation and measurable outcomes.

I’m a Machine Learning and Data Science intern who builds models that translate messy data into measurable impact. I’ve worked on predictive modeling, clustering, and NLP-driven insight extraction—always with an eye on speed, accuracy, and usefulness for stakeholders.

At Caterpillar, I developed a POD-RBF1 temperature field prediction model that delivered 1000x faster performance with 97.5% accuracy, working across 200K+ nodes. I also created a GPR-based model to save 200+ hours of computations and contributed to a 10% reduction in flow forces by optimizing hydraulic valve notch design using genetic algorithms.

In data science roles, I executed web scraping of property reviews and used BERT-powered Aspect-Based Sentiment Analysis to uncover critical customer purchase insights. I built interactive dashboards in Python (Matplotlib/Seaborn) to communicate sentiment trends and actionable results clearly.

I also led technical and organizational efforts, from RFM-based customer segmentation with K-Means on 500K transactions to running design and media strategy for IIT Madras’s flagship technical fest. I’m driven by experimentation, measurable outcomes, and collaborating closely to ship improvements that matter.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

Caterpillar

Jun 2025 - Aug 2025 (2 months)

Developed a faster, high-accuracy POD-RBF model for temperature field prediction on 200K+ nodes. Improved computational efficiency for flow force prediction and reduced flow forces by optimizing hydraulic valve notch design using genetic algorithms.

Machine Learning POD RBF Temperature Field Prediction Gaussian Process Regression Flow Force Prediction Genetic Algorithms Control Valves Valve Design

Machine Learning Intern

Vaidsys Technologies

May 2025 - Jul 2025 (2 months)

Developed a customer segmentation model using 500K retail transactions to support targeted marketing campaigns. Used RFM features with K-Means to identify customer segments and achieved a 15% projected conversion uplift in pilot regions.

Customer Segmentation K Means Retail Analytics data preprocessing

Data Science Intern

Smart Neev

Dec 2023 - Jan 2024 (1 month)

Built a web scraping pipeline for property reviews and used NLP to clean and preprocess review text for analysis. Implemented BERT-based aspect-based sentiment analysis and created Python dashboards to present sentiment trends and insights.

Web Scraping BeautifulSoup Natural Language Processing BERT Python Matplotlib SeaBorn Data Visualization

Design & Media Head

Shaastra

Led a 25+ member design team driving end-to-end creative strategy and branding for IIT Madras's technical fest.

Design Leadership Creative Strategy Branding Team Management

Events Core

Mitr

Managed a ₹2.3 crore budget to organize 32+ student well-being events, iterating based on feedback to improve programming.

Event Management Budget Management

SOC Finance

Owned a ₹1.5 Cr+ annual budget and maintained audit-ready financial governance with complete on-time payments. Supported financial modeling responsibilities including option pricing, portfolio optimization, risk management, and stochastic calculus.

Budget Management Financial Governance Audit Readiness Financial Modeling Options Pricing Portfolio Optimization Risk Management Stochastic Calculus