Masters in Business Analytics University of California, San Diego

Hi, I'm Sandeep

Welcome to my personal space. My journey in life has been deeply rooted in a growing passion for business analytics and data. Through various academic and professional experiences, I've focused on understanding how business analytics can be applied to solve real-world problems. This field, which combines my background in computer science with data-driven decision-making, has become a central part of my life. My work reflects this passion, as I continuously strive to learn more and apply my knowledge to practical challenges. Feel free to explore my portfolio to see how my experiences have shaped my approach to analytics and where this path is taking me.

Target Roles

Network Engineering
Data Analyst
Business Analyst
Sharepoint Developer

My Professional Journey

2024

Dexwell Inc, Carlsbad (Data Analyst)

Conducted comprehensive research on seawall integrity, identifying 15+ critical factors influencing their durability. Developed a detailed market analysis report, incorporating geospatial data to highlight buyer patterns and growth projections, with a projected 20% increase in seawall service demand over the next five years. Employed the XGBoost Time Series Model to create a predictive framework for monitoring seawater conditions, achieving 95% accuracy in predictive insights. Developed a comprehensive business model, including 5 detailed customer personas, cost analysis, and 3 pricing strategies, leading to a 15% increase in revenue projections.
2023

University of California SanDiego, California MSBA

Joined Masters in Business Analytics program at UCSD, focusing on data analysis, machine learning, and business intelligence. Developed a comprehensive understanding of data visualization, data mining, and predictive modeling. Conducted a capstone project on the impact of Seawalls for a potential Multi-Million dollar project with 10,000+ data points to identify key trends and insights. Earned a certification in Python, SQL, and Tableau, enhancing my data analysis and visualization skills. Conducted a comprehensive analysis of the e-commerce industry, identifying key trends and insights to inform strategic decision-making. Developed a predictive model for customer churn, achieving 85% accuracy in predicting customer behavior. Conducted a comprehensive analysis of the e-commerce industry, identifying key trends and insights to inform strategic decision-making. Developed a predictive model for customer churn, achieving 85% accuracy in predicting customer behavior.
2022

Infosys Limited, Hyderabad (Systems Engineer)

Led multiple teams in managing and optimizing the M365 Platform, including the successful transition of several high-complexity business applications to the platform. Enhanced system functionality and user experience by addressing Tier 1 issues and optimizing power applications. Streamlined the contract creation process for 300 sub-companies, significantly reducing time and increasing efficiency. Collaborated on complex projects using Power Automate, resulting in a 10% increase in project efficiency. Conducted workshops that improved user adoption and implementations, saving approximately 14 hours per month for 1,000 clients. Earned an internal certification as a Business Intelligence Associate, recognized for handling complex data. Led a project to create an alternative to Google Maps, reducing search times by 25% and enhancing user experience. Acquired extensive training in JavaScript, PHP, CSS, C#, .NET, and Angular, forming the foundation for future contributions.
2021

University of Petroleum and Energy Studies, India, Btech CSE

Graduated with a Bachelor of technology in Computer Science Engineering with specialization in Business Analytics and Optimization. Won 4th Place in Techstars startup weekend, developing a business plan for a new app which would solve the problem of food wastage in the University with a potential usage of 10,000+ customers. A member of Smart Analyzers a club totally dedicated to data analysis and visualization. A member of Computer Society of India (CSI) which is a professional body where I learned about the latest trends in technology. Treasure Hunt Runner up in the University Fest.
2020

WhiteLeo Industries,Raipur (Business Analyst)

Capitalized on the Covid-19 e-commerce surge, strategically marketing our app to expand reach and ensure sustained growth. Conducted a comprehensive survey of 250 consumers to understand their grocery buying habits and preferences, informing our targeted marketing strategies. In the heart of 2020, I embarked on a two-month journey with White-Leo Industries, immersing myself in the intricate world of comparative research and analysis.

Skills and Talents

Technical Skills

Python
R
SQL
Tableau
Power BI
Machine Learning
Deep Learning
Statistical Analysis
Data Visualization
Excel
Power Automate
Power Apps

Soft Skills

Communication
Decision Making
Conflict Resolution

Certifications

Projects

SeaPULSE: Enhancing Coastal Protection Through Predictive Analytics

The project focused on utilizing Dexwell's SeaPULSE platform to advance coastal protection by monitoring seawater conditions. The Rady School of Business interns conducted comprehensive research on seawalls and employed various advanced techniques to create a predictive framework. This framework leveraged data from seawater sensors, geospatial mapping, and machine learning models, such as the XGBoost Time Series Model, to anticipate and mitigate potential seawall issues. The project also involved developing a detailed market analysis report, business model, and strategic market entry plan, providing crucial insights for seawall maintenance and construction.

Team mates: Vishnu Mohan, Divyamsi Kunapareddy, Xintong Chen
Used Technologies: SeaPULSE Platform, Geospatial Mapping, Machine Learning, XGBoost Time Series Model

Enhancing Market Efficiency through Predictive Ratings: A Deep Dive into the Colombian Business Landscape

This research paper explores the development and evaluation of predictive models for rating businesses in Colombia, focusing on the utilization of various machine learning techniques. The study emphasizes the creation of new features from existing data to improve the predictive accuracy of business ratings. The project initially employs Logistic Regression and Random Forest models but transitions to a custom-built multi-input deep learning model using TensorFlow's Keras API to handle the dataset's complexity, particularly excelling in processing high-dimensional and diverse customer review data.

Team mates: Akhil Chitta, Abhinay Vemulapalli
Used Technologies: TensorFlow's Keras API, Logistic Regression, Random Forest, Deep Learning, TF-IDF

Samsung Mobile: Reducing Churn

This project focused on predicting customer responses and profitability through various machine learning techniques. The analysis involved the use of regression, neural networks, random forests, and XGBoost models to forecast customer reactions to marketing campaigns. The models were fine-tuned for optimal predictive accuracy, and individualized customer predictions were crafted to enhance engagement strategies. This approach resulted in a significant profit increase, totaling $802,010.

Team mates: Akhil Chitta, Ridhima Bansal, Alabhya Dahal
Used Technologies: Regression, Neural Networks, Random Forest, XGBoost

Enhancing Campaign Efficiency: Uplift Modelling

In this project, uplift modeling was employed to improve the accuracy and profitability of customer segmentation and marketing campaigns. The project integrated control and treatment datasets, ensuring balanced data through stratified sampling. Logistic Regression and Random Forest algorithms were utilized to achieve a 15% improvement in accuracy. An incremental profit analysis showed a 20% increase in profitability using uplift models compared to propensity models. Additionally, the project formulated optimal customer segmentation strategies, enhancing campaign efficiency by 25%.

Team mates: Akhil Chitta, Ridhima Bansal, Alabhya Dahal
Used Technologies: Logistic Regression, Random Forest, Uplift Modeling

Analyzing School Performance: SAT Scores and Mathematics Proficiency

This project focuses on analyzing school performance by utilizing data from a CSV file containing information about schools. The study involves several stages, starting with the calculation of top-performing schools based on average math scores. It then extends to the aggregation and analysis of total SAT scores across different schools and boroughs. The project employs data sorting, filtering, and statistical aggregation techniques to identify schools with high SAT scores and examine borough-level variations in performance.

Used Technologies: Python, Pandas, Data Aggregation, Statistical Analysis

Analyzing Netflix Movie Data: A Focus on 1990s Action Films

This project involves analyzing a dataset containing Netflix movie information, specifically focusing on movies released in the 1990s. The study includes filtering the dataset to isolate movies from 1990 to 1999 and analyzing the distribution of movie durations. Special attention is given to the count of action movies with a duration of less than 90 minutes during this decade. The project utilizes data exploration, filtering, and basic statistical analysis to derive insights from the Netflix dataset.

Used Technologies: Python, Pandas, Data Filtering, Statistical Analysis

Dexwell Inc, Carlsbad (Data Analyst)

University of California SanDiego, California MSBA

Infosys Limited, Hyderabad (Systems Engineer)

University of Petroleum and Energy Studies, India, Btech CSE

WhiteLeo Industries,Raipur (Business Analyst)

Technical Skills

Soft Skills

Google Certified Data Analyst

SAS Certification