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Shiv Mehrotra

@shivmehrotra

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Data science intern turning data into decisions with Python, SQL, and ML.

India

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What I'm looking for

I’m looking for a fast-paced team where I can apply Python/SQL, ML, and Tableau to deliver actionable insights—communicating clearly with stakeholders and improving decision-making impact through measurable outcomes.

I’m a versatile data science intern with proven analytical and technical proficiency, blending knowledge of databases, coding languages, and data visualization tools to deliver meaningful insights. In my internship, I applied statistical and algorithmic methods to real-world projects, helping drive a 25% increase in informed decision making and a 15% reduction in project timelines.

I manage, clean, and transform large datasets using Python and SQL, and I translate complex findings for non-technical stakeholders—driving outcomes like a 40% revenue increase and improvements in employee retention and customer loyalty. I’ve also built predictive analytics models and preprocessing pipelines that improved accuracy by 40% and reduced processing time by 20%, while Tableau dashboards helped increase data-driven decision-making efficiency by 30%.

Experience

Work history, roles, and key accomplishments

Data Science Intern

Vaidsys Technologies

May 2025 - Jun 2025 (1 month)

Applied statistical and algorithmic methods to deliver data-driven improvements, including a 25% increase in informed decision making and a 15% reduction in project timelines. Built predictive and feature-importance models to reduce employee turnover by 30% and improve employee satisfaction by 20%, while increasing model accuracy by 40% and reducing data processing time by 20%.

Python SQL Machine Learning Predictive Analytics data preprocessing Feature Importance Statistical Methods

Data Analyst

MedTourEasy

Jun 2024 - Jun 2024 (0 months)

Designed and implemented Tableau dashboards, improving leadership data-driven decision-making efficiency by 30% and reducing project metric analysis time by 25%. Developed and optimized SQL queries and R-based data cleaning/visualization workflows to improve analysis capabilities by 40% and reduce data preparation time by 60%.