Machine Learning Data Scientist/ Data Analyst

ISHMEET KAUR

*************@*****.*** 646-***-**** https://www.linkedin.com/in/ishmeet-kaur-a13bb4268/ TECHNICAL SKILLS

• Data Visualization: Tableau, PowerBI, Excel

• Database: MySQL, SQLite

• Data Manipulation & other: Tableau, PowerBI, Excel, Pandas, NumPy, Microsoft Office, Qualtrics

• Programming Languages: Python, JavaScript, HTML/CSS CERTIFICATIONS:

• GOOGLE: Data Analytics Certification

• LinkedIn Learning: From Excel to Tableau

• CLA: Programming essentials in C

• CLA: Programming essentials in C++

EXPERIENCE

Data Scientist Trainee, Shef Solutions LLC Nov -March 2025

• Studied machine learning algorithms, including linear regression, decision trees, and K-means clustering.

• Explored statistical aspects such as hypothesis testing and probability distributions.

• Wrote SQL queries to extract and manipulate data from a relational database.

• Became proficient with Python libraries_R for data analysis, such as Pandas, Numpy, and Scikit Learn.

• Learned techniques of data cleaning, preprocessing, and feature engineering. Project: In Data this project, Cleaning I worked with AI/on ML, cleaning Shef and Solutions analyzing LLC customer transaction data from an e-commerce platform to extract meaningful insights. The dataset Feb -March required 2025 significant preprocessing, including handling missing values through imputation strategies, identifying and removing duplicate records while maintaining data integrity, and detecting and addressing outliers in transaction amounts using statistical methods like Z-score and IQR. After data cleaning, I performed exploratory data analysis (EDA) through various visualizations, such as a missing value heatmap, transaction amount boxplots, age distribution histograms, category-wise sales analysis, and time series trends. My work resulted in a cleaner dataset, allowing for more accurate and actionable insights into customer spending behavior. This project reinforced my skills in data cleaning, preprocessing, statistical analysis, and visualization—key competencies in data analytics. AI-Analyst Intern, CIVET Global Technologies Pvt Ltd June-July 2023

• Collated datasets for language model training, adapting them for various neural network architectures

• Curated image datasets for CNNs and GANs, implementing state-of-the-art preprocessing techniques

• Trained neural network architectures, including RNN, LSTM, and hybridized transformer models within the AI framework

• Co-designed and implemented a hybridized RNN-LSTM-CNN-Transformer architecture, contributing to the development of an AI fashion assistant capable of processing natural language and images for intelligent fashion recommendations Project: University Course Performance Analytics September-October 2024

• Built Tableau dashboards to visualize trends in student performance and course outcomes

• Used SQL to extract and analyze data on enrollments, grades, and retention rates

• Cleaned and organized data in Excel/Google Sheets, performing statistical analysis to identify key trends

• Automated data updates between SQL and Tableau for real-time visualizations Project: Music Genre Classification Using Machine Learning October 2024

• Built and trained a machine learning model to classify songs by genre using a dataset of audio features.

• Utilized Python, Pandas, and TensorFlow in Jupyter Notebook to preprocess data, build, and evaluate the model.

• Applied ML concepts such as feature engineering, normalization, and model tuning to optimize predictions.

• Evaluated model performance using metrics like accuracy and confusion matrix to ensure robust genre classification. EDUCATION

Bachelor of Science, Ithaca College, Ithaca, NY May 2025 Major: Computer Science, Minor: Business Analytics Merit based scholarship

Peggy Ryan Williams Award for Academic and Community Leadership (PRWAACL) 2024 Relevant Coursework:

Principle of Computer Science I, Principle of Computer Science II, Intro to Data Structures, Discrete Structures, HCI: User Interface Design/Dev, Information and computer technology, Intro to computer organization & systems, Algorithms and Data Structure, Intro to Software Engineering, Intro to Web Development, Linear Algebra, Intermediate Statistics, Databases & Systems, Intermediate Business Analytics, Machine Learning

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