Pranjal Jain's Portfolio

About Me

As a dedicated student pursuing a Master of Science in Business Analytics and Project Management at the University of Connecticut, my academic and professional journey is built on a diverse foundation—beginning with a Bachelor’s degree in Mechanical Engineering and further honed through rigorous coursework in Data Science, Predictive Analytics, Statistics, Quantitative Analysis, Data Engineering, and Big Data Management.

My professional experience includes a Systems Engineer role at Tata Consultancy Services, where I developed and implemented a CI/CD test utility using Jenkins that reduced infrastructure costs by $100K, automated report generation to save 85% of reporting time, and led multiple proof-of-concept projects to enhance data privacy and quality through SQL-driven data cleaning initiatives.

With solid achievements and certifications in SQL, Python, JIRA, and Agile methodologies—alongside proficiency in Tableau, Power BI, Azure Data Factory, and Databricks—I am well-prepared to tackle complex challenges at the intersection of business analytics and project management.

I am also actively engaged in academic projects that apply analytical techniques to real-world problems, such as healthcare claims database optimization, risk prediction in car insurance claims, and nutritional analysis of consumer products. When I’m not working on data models, I enjoy playing outdoor sports, watching movies, and exploring emerging technologies.

Experience and Education

I never stopped learning and applying. Take a look at my learnings and accomplishments

Data Science Associate Graduate Student Consultant Systems Engineer Education

International Medical Crisis Response Alliance (IMCRA), Norwalk, CT

Data Science Associate

(Jan 2025 – Present)

Spearheaded automated data pipeline with Azure Data Factory & Databricks to process 5 GB+ of oceanic research data (SIDS 4), cutting ingestion time by 40%.
Improved data quality via schema validation & deduplication in PySpark, reducing manual cleanup efforts by 60%.
Ran optimized SQL queries in Synapse Analytics to deliver actionable marine policy insights, boosting retrieval efficiency by 30%.
Built dynamic dashboards & reports to engage researchers and international delegates, increasing stakeholder confidence.
Led fundraising initiatives and diplomatic discussions to secure project funding and expand visibility for ocean data efforts.

PepsiCo, Valhalla, NY

Graduate Student Consultant

(Aug 2024 – Dec 2024)

Developed a predictive modeling framework to forecast PET bottle performance metrics, enabling data-driven process optimizations that reduced material waste and costs.
Designed interactive Tableau Stories synthesizing EDA and predictive analytics for real-time visibility into manufacturing inefficiencies, empowering packaging team decisions.

Tata Consultancy Services, Indore, India

Systems Engineer

(Apr 2021 – Jun 2023)

Built Jenkins-based CI/CD test utility, cutting infrastructure costs by $100 K and visualized savings using Matplotlib & Seaborn.
Automated performance-metrics reporting via Jenkins, slashing report-generation time by 85% and applying Python for statistical analysis.
Delivered knowledge-transfer sessions on testing methodologies and script optimization to 40+ cross-functional teams.
Led PoCs to enhance data privacy & quality with TCS Mastercraft DataPlus and SQL, managing a team of 5 in data cleaning and wrangling.

University of Connecticut, Hartford, CT

M.S. in Business Analytics & Project Management

(May 2025)

Relevant Coursework

Data Science
Predictive Analytics
Statistics
Quantitative Analysis
Data Engineering
Big Data Management

Academic Projects

Projects I've Led

Healthcare Insurance & Claims Data Analysis

Engineered a healthcare claims database with ERD, BeautifulSoup for extraction, and PostgreSQL DDL/DML—improved processing speed by 40% and accuracy by 15%.

Optimizing Risk Prediction in Car Insurance Claims

Cleaned & preprocessed 100K+ column dataset, applied feature engineering and outlier detection to refine to 20 predictive features.
Evaluated ML models—GBT achieved 83% accuracy, 10% lift over alternatives.

Statistical Nutritional Analysis

Analyzed 55,000+ cereal product data points using R (linear regression, T‑tests, Z‑tests) to predict calorie content with 80% accuracy.
Visualized findings in a Tableau dashboard viewed by 200+ users, influencing healthier food decisions.

Personal Portfolio Tracker

Built an automated ETL pipeline using Python, Kite Connect API, and Power Automate to refresh Power BI dashboards daily.
Streamlined portfolio monitoring for Zerodha accounts by integrating CSV data storage on OneDrive.