About Me
Hi, I am Anjali. I am a Software Engineer with experience in backend development using Java, Python, and REST APIs, with a strong focus on building reliable, well-structured systems. After starting my career in software engineering and contributing to complex technical systems, I expanded my domain expertise through a role in technical audit — where I applied engineering judgment to real-world system risk, reliability, and compliance challenges.
Experience
Research Intern
Indraprastha Institute of Information Technology, DelhiMay 2021 – Dec 2021 · IIITD Networks Lab | Delhi
Education
Master of Science in Management Information Systems
University at Buffalo, New YorkJul 2023 – Jun 2024 · United States
Relevant Courses: Data Warehousing, System Design and Analysis, Relational Database Systems, Salesforce CRM, Predictive Analytics, Web Analytics, Cloud Computing and Data Visualization.
Master of Technology in Computer Science
Indraprastha Institute of Information Technology, DelhiAug 2020 – June 2022 · India
Relevant Courses: Graduate Algorithms, Machine Learning, Android Development, Data Mining and Information Retrieval.
Bachelor of Technology in Electronics and Communication
Deenbandhu Chhotu Ram University of Science and Technology, SonepatJun 2013 – May 2017 · India
Relevant Courses: Data Structures and Algorithms, Programming in C++, Database Systems, Operating Systems and Computer Networks.
Skills
Python
SQL
Tableau
AWS
Java 8
HTML
CSS
Javascript
MongoDB
Golang
Docker
Git
Linux
GitHub
Projects
E-commerce Analytics Dashboard
Performed exploratory data analysis (EDA) on Google Merchandise Sales Data to analyze key metrics like visitor behavior, website growth, and user engagement, utilized SQL and Python to extract data from Google BigQuery, and measured the overall goal conversion rate of 1.3%. Completed country-wise analysis and visualized using Google Looker Studio, determining the United States as largest market with 94.4% of customers and 59.8% of visitors, followed by Canada
Retail Analytics Dashboard
Architected data warehouse for retail analytics by consolidating sales, customer and supplier data using Oracle SQL Server employing dimensional modeling and star schema. Established optimized ETL workflows using Talend to develop Power BI dashboards for real-time insights and decision-making, leading to targeted marketing campaigns which boosted sales by 15%
Twitter Sentiment Analysis
• Built Twitter Sentiment Analysis project in Python, utilizing advanced techniques such as Tf-Idf, GloVe, and Word2Vec for in-depth analysis of Twitter data. Employed Logistic Regression, Naïve Bayes, SVM, and MLP classifier models to accurately predict sentiment in tweets, contributing to nuanced sentiment understanding.
Housing Price Prediction using Predictive Analytics
Executed predictive analytics on 100000 rows of housing prices data with 10+ attributes. Undertook data wrangling, cleansing, preprocessing, PCA, applied Logistic Regression, achieving 92% F1 score for price prediction, also deployed on hugging face
