Hi I'm Jasdeep Singh Jhajj and I am a

Data Enthusiast

Data Analyst

Data Engineer

Machine Learning Engineer


View Resume


ABOUT ME


Predicting trends, analyzing patterns, and still forgetting where I left my keys. Because even data pros have their "human moments." 😄

View My Projects

Github Repo

Areas of Core Competence

Designing & developing data-driven software and business solutions, extracting actionable and predictive insights from data, and automating high volume, repetitive business tasks and processes.



Machine Learning & AI

Proficient in designing and implementing machine learning models for predictive analytics, sentiment analysis, and emotion recognition. Skilled in using Python, TensorFlow, and scikit-learn to build and optimize algorithms.

Data Visualization & Analysis

Experienced in creating interactive dashboards and visualizations using tools like R, Shiny, and Tableau. Adept at uncovering trends and patterns in large datasets to drive data-informed decisions.

Software Engineering & DevOps

Strong expertise in building scalable microservices, CI/CD pipelines, and containerized applications using Docker, Kubernetes, and Jenkins. Focused on improving system efficiency and deployment processes.

Natural Language Processing (NLP)

Skilled in leveraging NLP techniques for sentiment analysis, text classification, and language modeling. Proficient in using libraries like NLTK, spaCy, and Hugging Face for advanced text processing tasks.

Skills

Here are some of my skills on which I have been working on for the past 3 years.

Programming Languages

Python R Go SQL C++ Bash

Machine Learning & AI

TensorFlow Scikit-learn Keras PyTorch NLP Deep Learning

Cloud & DevOps

Docker Kubernetes Jenkins Git JIRA Confluence CI/CD Helm SonarQube Microservices

Data Visualization

Tableau Excel R Shiny Quarto Ggplot2 Matplotlib Plotly

Education & Experiences

Education

Masters of Science (M.S.)

Jan 2024 - May 2025

M.S. in Data Scinece

University of Arizona

Relevant Courses: Machine Learning, Data Analysis and Visualization, Neural Networks, Applied Natural Language Processing, Data Mining, Healthcare Data Science, SQL/NoSQL Databases

Bachelors of Engineering (B.E)

Jul 2017 - Jun 2021

B.E in Electronic and Communication Engineering

Thapar Institute of Engineering and Technology, Punjab, India

Relevant Courses: Computer Programming, Machine learning, Data structure and algorithms, Probability & Statistics, Object Oriented Programming, Mathematics (Calculus, Differential Equation, Linear Algebra), Operating Systems

Professional Experience

AI Integration Engineer for Healthcare Applications

Jan 2025 - Present

University of Arizona Health Sciences, Tucson | Part-time

Advancing Data-Driven Medical Education Through AI Solutions

  • Developed AI-driven data generation pipelines to automate the creation of structured clinical scenarios, enabling richer datasets for educational analysis and insights.
  • Leveraged the ChatGPT API for generating structured patient case data, supporting richer analytics and minimizing manual input by educators.
  • Implemented context-aware systems to ensure the integrity and accuracy of dynamically generated data, enabling reliable downstream analysis and reporting.

Systems Engineer

Jul 2021 - Dec 2023

Tata Consultancy Services, India | Full-time

Driving Scalable Data Pipelines, DevOps Automation, and Analytics Integration

  • Designed and optimized data pipelines using Python, Go, and SQL, improving ETL workflows and delivering high-quality, structured data for analytics across Ericsson’s global systems.
  • Built automated CI/CD pipelines with Jenkins, Helm, and Git, accelerating deployment of data-driven applications and reducing release cycles by 21%.
  • Deployed containerized data services and microservices with Docker and Kubernetes, ensuring 99.9% system uptime and supporting scalable, analytics-ready infrastructure.
  • Collaborated with cross-functional Agile teams to integrate data requirements, enhance system monitoring, and align engineering and analytics goals.
  • Conducted in-depth data analysis on system performance and pipeline metrics, improving data processing efficiency by 15% and supporting actionable insights.

Industrial Python Training Program

Jan 2021 - Jun 2021

ThinkNEXT Technologies

Python, Django, and Full-Stack Web Development

  • Developed an end-to-end e-commerce clothing website using Python, Django, and SQL, enabling seamless product browsing, cart management, and checkout functionality
  • Built a responsive front-end with HTML, CSS, and JavaScript, and integrated RESTful APIs for dynamic data retrieval and updates
  • Optimized backend performance using C++ and SQL, reducing load times and improving scalability for large product catalogs

Projects


Uncovering Big Tech Stock Prices (2010–2022)

R Quarto Data Visualization TidyTuesday Dataset ggplot2 Trend Analysis
  • Analyzed 12 years of stock prices (2010–2022) for 14 major tech companies, focusing on trends around significant events like COVID-19
  • Processed 45,000+ data points on stock prices and trading volumes using R and Quarto, creating interactive visualizations (bar plots, line plots) to highlight trends and returns
  • Identified companies with the highest/lowest pandemic impact on stock prices and uncovered patterns in positive gain days over the 12-year period
  • Provided actionable insights for stakeholders to make data-driven decisions and optimize strategic planning

GitHub Repo
Beyond Likes and Dislikes: Unveiling YouTube Comment Sentiment

Python Scikit-Learn SVM NLP Pandas Matplotlib
  • Built a sentiment analysis tool using Python, ML, and NLP to classify millions of YouTube comments, predicting like percentages with 84.17% accuracy
  • Optimized an SVM model to achieve 0.86 precision, evaluating accuracy and recall as key performance metrics
  • Analyzed sentiment trends to uncover patterns in viewer engagement, helping creators improve content relevance and optimize strategies
  • Enabled scalable, automated sentiment analysis, replacing manual efforts and providing actionable insights for content creators

GitHub Repo
Meteoric Fall: A Comet-ment to Data

R Shiny Data Visualization Quarto Leaflet NASA Dataset
  • Developed an interactive Shiny app to explore and analyze 45,716 meteorite landings from NASA’s Open Data Portal, enabling users to visualize global meteor impacts and trends
  • Created dynamic visualizations, including interactive maps and animated line graphs, to showcase meteor distributions across 5 continents and their correlation with historical events
  • Analyzed patterns in meteorite types, masses, and locations, uncovering insights into celestial events like meteor showers and their impact on Earth
  • Improved accessibility of meteorite data for researchers and educators, with the app accessed by 200+ users

GitHub Repo
Emotion Predictor using EEG

Python Machine Learning K-Nearest Neighbors (KNN) Scikit-Learn Pandas EEG Signal Processing
  • Built an EEG-based emotion predictor using Python and Machine Learning to classify emotional states for mood enhancement and human-AI interaction
  • Processed raw EEG signals and extracted features to train a K-Nearest Neighbors (KNN) model for accurate emotion classification
  • Enabled real-time emotion prediction, providing insights into user mood and enhancing personalized AI interactions

Reach Out to Me!

If you are interested in collaborative value creation, give me a call or send an email and I will get back to you as soon as possible.

Call

+1 (520) 460-2999

Email

jasdeepjhajj@arizona.edu

LinkedIn

linkedin.com/in/jasdeep-jhajj

GitHub

github.com/Jasdeep-Singh-Jhajj