J.D. Edwards World Programmer/Analyst Candidate

Devansh Desai

249-***-**** *******.*******@*****.*** LinkedIn GitHub Kaggle

Professional Summary

Graduate student in Applied Modelling & Big Data Analytics at Trent University with hands-on experience in machine learning, deep learning, and data visualization. Skilled in building predictive models, conducting statistical analysis, and developing data-driven applications using Python and modern tools.

Education

Trent University Ontario, Canada

M.Sc in Applied Modelling and Big Data Analytics Jan 2024 – Apr 2025

Gujarat Technological University Gujarat, India

B.E in Computer Engineering Jul 2019 – Jun 2023

Work Experience

Marker/Grader Mar 2024 – Apr 2024

Trent University – Ontario, Canada

Evaluated coursework for managerial accounting (ADMN-021H), demonstrating strong analytical reasoning.

Gained precision and attention to detail in reviewing financial and business data.

Social Media Specialist Oct 2023 – Dec 2023

One08 Agency– Melbourne, Australia

Planned and executed data-driven content strategies, increasing engagement by 30%.

Implemented advanced analytics tools to track campaign performance, reducing CAC by 50%.

Improved conversion rates by 15% through continuous optimization based on performance metrics.

Data Science Intern Feb 2023 – May 2023

Grownited PVT LTD – Gujarat, India

Developed and deployed ML models for a crop recommendation web application using Random Forest and XGBoost.

Enhanced prediction accuracy by 15% through iterative tuning and feature engineering.

Conducted data wrangling, EDA, and visualization to improve insights and application usability.

Digital Strategist Jun 2021 – Apr 2022

Abhyant Solutions – Gujarat, India

Led marketing campaigns promoting NEAR cryptocurrency, increasing brand awareness by 40%.

Utilized competitor analytics to identify growth opportunities, resulting in a 30% increase in web traffic.

Reduced cost-per-click by 20% by optimizing content based on audience insights.

Projects

Crop Recommendation System (Github)

Built a machine learning model (Random Forest, SVM) to suggest optimal crops based on NPK values.

Achieved 90% prediction accuracy and deployed via Flask web app.

Plant Disease Detection (Github)

Built a Convolutional Neural Network (CNN) to classify plant diseases from leaf images.

Integrated into a web app allowing real-time image uploads and predictions.

EDA & Hypothesis Testing (Notebook)

Conducted exploratory data analysis and applied hypothesis testing techniques (t-tests, ANOVA).

Derived actionable insights from real-world datasets using Pandas, Seaborn, and Scipy.

Technical Skills

Programming: Python, Java, C++, Go, JavaScript, HTML, CSS

Libraries & Frameworks: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras, XGBoost, CNN, RNN, Neural Networks

Data Science: EDA, Data Cleaning, PCA, Dimensionality Reduction, Clustering, Linear Models

Statistical Analysis: Hypothesis Testing, Regression, Inference, Time Series Analysis

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