Data Science Analyst

Dhruv Dinesh

§ https://github.com/Dalgom** ï https://www.linkedin.com/in/dhruvdinesh/ # *****.**********@*****.*** Education

Rutgers University New Brunswick Graduated May 2025 Bachelor of Arts in Computer Science and Data Science, Magna Cum Laude GPA: 3.7/4.0 Relevant Coursework

Courses: Data Structures and Algorithms, Computer Architecture, Discrete Structures I & II, Linear Algebra, Regression Methods, Statistical Learning, Software Methodology, Intro to Data Science, Databases Skills

Languages: C/C++, Java, Python, JavaScript, HTML/CSS, SQL, R Tools: Git/GitHub, NodeJS, Pandas, NumPy, Matplotlib, JavaFX, Google Cloud Platform, BigQuery, Oracle Database Experience

Data Analyst Intern May 2024 – August 2024

C&S Wholesale Grocers Hybrid

• Analyzed cost and invoice data across multiple wholesalers to identify pricing discrepancies and discount opportunities.

• Leveraged Google Cloud Platform (BigQuery) and Oracle Databases to extract and process large datasets using SQL.

• Developed Python-based analytics notebooks and interactive dashboards to visualize cost structures and discount trends.

• Investigated pricing variations stemming from regional freight costs and contractual terms, driving enhanced cost efficiency strategies.

• Collaborated with cross-functional business teams to refine discount models based on geographical and contractual factors, fostering data-driven decision-making.

Projects

World Cup 2022 Match Predictor Python, Pandas, Scikit-learn Aug 2023

• Developed a model to predict match outcomes using FIFA rankings and historical match data.

• Engineered features (ranking/goal differentials) and employed Gradient Boosting & Random Forest.

• Achieved an AUC of 0.79 on the test set (0.86 on training) by tuning hyperparameters (learning rate, max depth).

• Simulated tournament stages, visualizing performance via AUC-ROC curves & confusion matrices. Spotify Top 50 Dashboard Node.js, Express, OAuth 2.0, JavaScript Jun 2023

• Built a full-stack web app to display top artists/tracks/genres using the Spotify API.

• Integrated OAuth 2.0 for secure login & built a RESTful backend for personalized data.

• Implemented a dynamic UI with tab navigation, time-range selection, and a dark mode toggle. Last.fm Data Analysis & Prediction Python, Pandas, Scikit-learn Jul 2023

• Processed and analyzed music listening history from Last.fm using API requests & JSON parsing.

• Created data visualizations (heatmaps/time series) with Matplotlib & Seaborn.

• Built Random Forest models to predict hourly scrobbles & classify genres (54.5% accuracy).

• Leveraged feature engineering (day/hour, user tags) to boost predictive performance. Twitter Sentiment Analysis Python, NLP, Scikit-learn Sep 2024

• Built a pipeline with Tweepy to collect large-scale tweet data for sentiment analysis.

• Applied NLP (tokenization, lemmatization) & VADER to classify tweet sentiments.

• Used PCA on a document-term matrix, visualizing insights with heatmaps & scatter plots. Airport Management Database SQL, Database Design Apr 2024

• Designed a relational DB for flights, airport ops, and passenger data with role-based access.

• Implemented user authentication (admin/staff/passengers) & advanced SQL queries for reservations.

• Developed waitlist logic for fully booked flights, enabling seamless passenger management.

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