Hi! I am 👋

Panshul Saraswat

Empowering decisions through data-driven analysis

About Me

Hi, I'm Panshul Saraswat, a data-driven professional with a Master's in Business Analytics from the University of Illinois Urbana-Champaign. With expertise in data analysis, machine learning, and AI-powered solutions, I am passionate about transforming raw data into actionable insights that drive measurable business growth. My achievements include a 40% improvement in analysis accuracy, a 50% reduction in processing time, and a 30% boost in grant relevancy—showcasing my ability to optimize processes and deliver impactful results.

I thrive on bridging the gap between technical and non-technical audiences, ensuring data-driven decisions are accessible, actionable, and strategically aligned. From building robust data pipelines to deploying interactive dashboards, I enjoy creating innovative solutions that enhance decision-making and streamline workflows.

Beyond work, I'm an avid FPS gamer and an enthusiastic traveler, always seeking fun, adventure, and new experiences. I believe growth stems not only from professional challenges but also from exploring diverse perspectives and opportunities life has to offer.

EDUCATION

Master of Science in Business Analytics

2023-2024

GPA: 3.85/4.0

Bachelor of Technology in Electronics and Communication Engineering

2017-2021

GPA: 7.61/10.0

Relevant Coursework:

Database Management, Predictive & Statistical Analysis, Business Intelligence, Decision Modeling, Data Mining, Data Storytelling, Data Visualization, Machine Learning, Supply Chain Management, Big Data Finance, Financial Data Management Analysis

Expertise & Skills

Areas of Expertise

Python Programming

SQL

Data Science

Data Analysis

Machine Learning

Data Visualisation

Data Engineering

NLP

Tech Stack

Data Science and ML

Software Development

Cloud and Databases

Data Visualisation

Certifications

Microsoft Azure Fundamentals

Microsoft

Cloud computing concepts, core Azure services, security, privacy, compliance, trust, and pricing and support

KNIME Analytics Platform

Basic Proficiency

Data analytics, machine learning, and data visualization using the KNIME platform

Inferential and Predictive Statistics

Business Analytics

Statistical analysis, hypothesis testing, regression analysis, and predictive modeling for business decisions

Work Experience

Santech Solutions

At Santech Solutions, I developed iSmart, an AI-powered healthcare contract analysis tool integrated with iNetwork. By implementing machine learning models and vector databases, I helped automate complex contract workflows—reducing manual review time and improving accuracy. This led to enhanced decision-making and operational efficiency across contract management processes.

Data Analyst

August 2024 - Present

Princeton, NJ

Business Analyst

January 2024 - May 2024

Champaign, IL

Discovery Partner Institute (DPI)

Led a 9-member team to develop an AI and LLM-powered tool for project and grant tracking at DPI, leveraging AI algorithms and Python web scraping to increase grant relevancy and effectiveness by 30%.

Designed and deployed a comprehensive data extraction and summarization system using Azure Chat OpenAI, advanced NLP models, and PDF extraction, enhancing data retrieval accuracy by 40% and halving processing time.

Our work was recognized and featured in an article by the Gies College of Business. Read more about the project here

Horizon Hobby

Conducted an in-depth analysis of customer data using segmentation techniques to enhance targeting strategies and identify market segments, resulting in a 30% improvement in targeting efficacy.

Developed and implemented tailored marketing strategies for identified segments, including textual analysis of product descriptions, which refined customer personas and significantly boosted business growth.

Student Consultant

August 2023 - May 2024

Champaign, IL

Software Engineer/Analyst

March 2021 - November 2022

Bangalore, India

Capgemini

At Capgemini, I worked on the Devlink productivity analytics tool, using Tableau and Excel to drive team performance insights. I also enhanced embedded systems stability by reducing driver errors by 30%, using advanced debugging tools like Lauterbach/JTAG. My contributions included collaborating cross-functionally to resolve memory-sharing issues, achieving a 95% issue resolution rate.

Rajasthan Vidyut Prasaran Nigam(RVPN)

Collaborated on SLDC operations, utilizing real-time data from multiple sub-load stations to ensure effective, efficient and transparent power system control and safeguard electrical grid stability.

Successfully completed a comprehensive training program on SCADA systems, gaining in-depth knowledge and practical experience in system monitoring and control.

Intern

June 2019

Jaipur, Rajasthan, India

Intern

December 2018

Panchkula, Haryana, India

Bharat Electronics Private Ltd.

Researched and analyzed SMD technology and electronic systems utilized in the defence sector during the internship at Bharat Electronics Limited, gaining valuable knowledge and understanding of cutting-edge technologies.

Academic Projects

Real-Time NBA Data Analytics Pipeline

Developed a data pipeline using Apache Kafka, Apache Spark, and InfluxDB to analyze live NBA game statistics. Created interactive Grafana dashboards for real-time updates and insights, boosting fan engagement and supporting gameplay decisions.

Apache Kafka Apache Spark InfluxDB Grafana Python

View on GitHub

Visual Analytics for Blockchain Sales

Developed visual analytics tools to track and analyze blockchain sales data, providing insights into market trends and sales performance.

Interactive Dashboards

BAYC NFT Analysis Dashboard

CryptoPunks Market Analysis

Fidenza NFT Market Insights

Python D3.js Web3.py SQL Tableau

View on GitHub

Statistical Modeling for Property Valuation

Conducted data cleaning to handle missing values, outliers, and inconsistencies, and identified factors influencing housing prices. Used Lasso regression to predict housing prices, achieving an accuracy of 92%.

Python Scikit-learn Pandas NumPy Matplotlib

View on GitHub

Yelp Dataset ETL and Analysis

Implemented an ETL process to extract, transform, and load Yelp data for analysis, providing insights into customer reviews and business performance.

Python Apache Spark PostgreSQL NLTK Pandas

View on GitHub

Cloud-Optimized Data Ecosystem Project Integration

Implemented scalable MongoDB clusters on the cloud for efficient data storage and management. Integrated Yelp data from Kaggle and real-time NFT sales data from Flipside via a Python API, improving data-driven decision-making by 30%.

MongoDB AWS Python Docker Kubernetes

View on GitHub

Determining the Success of an IPO

Analyzed factors contributing to the success of IPOs using historical data and statistical models to predict future performance.

Python R SQL Tableau Machine Learning

View on GitHub

Discovery Partner Institute (DPI)

Developed tools for project and grant tracking, enhancing grant relevancy and effectiveness by 30% using AI and LLM-powered solutions.

Python OpenAI Azure LangChain FastAPI

View on GitHub

Energy Production Trends Analysis

Analyzed energy production data to identify trends and patterns, providing insights into renewable energy sources and their impact on the market.

Python Pandas Matplotlib Seaborn Scikit-learn

View on GitHub

Leadership & Publications

Featured Project: AI Tool for Streamlining Industry-Academia Collaboration

As part of the Gies MSBA program, I led the development of an innovative AI-powered tool designed to streamline collaboration between industry and academia. This project involved leveraging advanced AI models, including natural language processing and vector storage technologies, to enhance efficiency in project and grant management.

Our work was recognized and featured in an article by the Gies College of Business. Read more about the project here

Gies College of Business - MSBA Student Leadership Council

Acted as a liaison for over 100 students, resolving conflicts and creating a support system that provided academic resources to enhance student success.

Design and Implementation of Approximate Divider For Error-Resilient Image Processing Applications

Presented a research paper at the IEEE-sponsored conference on the design and implementation of an approximate divider for error-resilient image processing applications, utilizing Cadence Virtuoso, MODELSIM, and MATLAB for VLSI circuit design.

Click here to read the full paper

Contact

Panshul Saraswat

Email

panshul590@gmail.com

Location

Champaign, IL

Phone

(+1) 217-904-2035