KUMBHA RAJESHBABU
Entry Level Graduate | Machine Learning Engineer • Hyderabad • r******************@gmail.com • +91*******654 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Scientist with 0 years of experience applying Python, SQL and machine learning techniques to build predictive models and convert raw data into actionable business insights. Experienced in end-to-end project work including data cleaning, feature engineering, model development (classification and regression), evaluation and communicating findings to stakeholders.
Technical Skills
Programming Languages: Python
Frameworks and Libraries: Pandas,NumPy,scikit-learn,Model Evaluation,Hyperparameter Tuning,Feature Engineering,Matplotlib,Seaborn
Databases: SQL
Cloud and DevOps: Microsoft Azure,Azure AI concepts,OpenAI API
Data and Analytics: Data Preprocessing,Exploratory Data Analysis,Logistic Regression,Decision Trees,Random Forest,Ensemble Methods,Regression Models,Classification,Data Visualization for Stakeholders
Tools and Methodologies: Jupyter Notebook,Git,GitHub
Work Experience
BCG Data Science Job Simulation on Forage
Data Science Simulation Participant
January 2025 – January 2025
Completed a BCG management-consulting style data science simulation on Forage focused on customer churn analysis and predictive modeling to support consulting recommendations.
Tech Stack: Python, Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, Jupyter Notebook, GitHub
- Built an end-to-end churn prediction pipeline using Python, Pandas and NumPy to ingest, clean and prepare customer datasets for modeling.
- Performed exploratory data analysis and visualized churn drivers with Matplotlib and Seaborn to surface actionable patterns for stakeholders.
- Engineered predictive features and constructed scikit-learn pipelines to transform raw variables into model-ready inputs for classification.
- Trained and optimized a Random Forest classifier with grid search and cross-validation in scikit-learn, achieving 85% accuracy on churn prediction.
- Evaluated model performance using precision, recall and ROC-AUC, and recommended interventions to reduce high-risk customer churn segments.
- Documented reproducible analysis and delivered an executive summary for the Associate Director; stored notebooks and code in GitHub for handover.
Projects
Titanic Survival Prediction
Tools Used: Python, Jupyter Notebook, Pandas, scikit-learn, Feature Engineering, Logistic Regression, Decision Trees, Ensemble Methods
- Developed classification models in Python and Jupyter Notebook to predict passenger survival using demographic and voyage features.
- Engineered and selected features, applying transformations and pipelines that reduced dataset dimensionality by 30% and improved model signal.
- Compared logistic regression, decision tree and ensemble approaches and optimized hyperparameters to lower false negatives on the validation set.
- Analyzed correlations between survival and attributes such as age, passenger class and gender to produce interpretable model insights for reporting.
Sales Prediction | July 2023 – August 2024
Tools Used: Python, Pandas, Regression Models, Feature Selection, Matplotlib, Seaborn
- Built a sales forecasting model using regression techniques to predict future sales from historical transactional and seasonal data.
- Improved preprocessing and feature selection steps to reduce model training time and surface the most predictive variables.
- Trained and validated regression models, reporting an achieved forecasting accuracy of 92% on holdout data.
- Visualized trends and created dashboards with Matplotlib and Seaborn to communicate actionable insights that informed sales strategy.
Education
KL University
Bachelor of Technology in Artificial Intelligence and Data Science • April 2020 – May 2024
Narayana Junior College
Board of Intermediate Education • June 2018 – March 2020
STZP High School
SSC (10th class) • June 2017 – April 2018
Certifications
Python for Data Science Bootcamp
Microsoft Azure AI Fundamentals — Microsoft
Microsoft Azure Fundamentals — Microsoft
APSSDC Machine Learning certification program — APSSDC
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