Mohith Reddy Kandakatla

Mohith Reddy Kandakatla

Master of Science in Data Science

Regis University

Expected Graduation: Spring 2026

About Me

I am Mohith Reddy Kandakatla, a graduate student pursuing a Master of Science in Data Science at Regis University. My academic interests include machine learning, data analytics, predictive modeling, and artificial intelligence. I enjoy working with data to solve real-world problems and uncover meaningful insights through statistical analysis and visualization.

Throughout my studies and professional experience, I have worked on projects involving time series forecasting, machine learning, and large-scale data analysis. Previously, I worked at Cognizant as a Data Analyst, where I was responsible for reviewing and validating business listings on Google Maps based on quality and policy guidelines.

My career goal is to build expertise in data science and machine learning while contributing to data-driven decision-making. I am particularly interested in predictive analytics, data engineering, and AI applications that help organizations solve complex business challenges.

Technical Skills

Programming Languages

Python, SQL, R, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, XGBoost, LSTM, Git, GitHub, Jupyter Notebook, VS Code, Data Visualization, Machine Learning, Time Series Forecasting, Feature Engineering, Statistical Analysis, Data Mining, Tableau, Power BI

Tools & Frameworks

Git, GitHub, Jupyter Notebook, VS Code, Pandas, NumPy

Machine Learning

Scikit-learn, TensorFlow, Keras, XGBoost, LSTM

Practicum Projects

MSDS 692

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Regis University | MSDS 692 | Spring 2025
MSDS 696

Modeling the Spread of Rent Inflation Across Counties in New York Using Spatial Analysis and Machine Learning

Data Science Machine Learning Time Series Forecasting Spatial Analysis XGBoost LSTM Rent Inflation.

This project analyzes the spread of rent inflation across New York counties using spatial analysis and machine learning. Data from multiple sources were collected, cleaned, and merged to study the impact of factors such as personal income, housing units, and investment on rent growth. ConvLSTM, XGBoost, and LSTM models were used to understand and predict rent inflation patterns over time.

Regis University | MSDS 696 | Spring 2026

Get In Touch

Let's Connect

Feel free to reach out for collaboration opportunities, questions about my projects, or just to connect!

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I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.

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