VARUN TEJA

[email protected] • 7780770475 • Hyderabad, India

PROFESSIONAL SUMMARY

Data Scientist with 1 year of industry experience in supporting real-time machine learning projects. Strong in data preprocessing, exploratory data analysis (EDA), feature engineering, model building, and evaluation, working under guidance of senior data scientists. Experienced in applying CRISP-ML(Q) methodology to solve business problems using Python and Machine Learning.

WORK EXPERIENCE

Data Scientist
04/2025 - Present
Internity IT Service Private Limited
• Worked as a junior data scientist on a real-time customer analytics project
• Performed data cleaning, preprocessing, and EDA on structured datasets
• Handled missing values, outliers, feature scaling, and encoding techniques
• Assisted in feature engineering to improve clustering performance
• Implemented machine learning models under guidance of senior team members
• Evaluated model performance using Silhouette Score and Elbow Method
• Interpreted model results and shared insights with senior data scientists
• Supported model deployment by validating predictions on new data
• Maintained documentation following CRISP-ML(Q) lifecycle

EDUCATION

B.Tech – Civil Engineering
01/2018
VIT University

SKILLS

Technical Skills: Python, NumPy, Pandas, Scikit-learn, Machine Learning, Random Forest, XGBoost, Natural Language Processing, Deep Learning, Exploratory Data Analysis, Feature Engineering, Model Evaluation, Data Visualization
Soft Skills: Analytical Thinking, Problem Solving, Attention to Detail, Collaboration, Adaptability
Tools: Git, Jupyter Notebook, VS Code, Power BI, Excel, Snowflake, AWS S3
Other: CRISP-ML(Q), Data Science Methodologies, Basic CNN, TF-IDF, N-Grams, Snowpipe, Streams, Tasks

PROJECTS

Customer Segmentation Using Machine Learning
Technologies: Pandas, NumPy, K-Means clustering
• Understood business problem related to customer grouping for targeted marketing
• Cleaned and preprocessed customer data using Pandas and NumPy
• Performed EDA to identify customer behavior patterns
• Implemented K-Means clustering for customer segmentation
• Identified optimal clusters using Elbow Method and Silhouette Score
• Interpreted clusters from a business perspective
• Supported deployment by testing cluster assignment for new customers

CERTIFICATIONS

Data Science & AI – 360DigiTMG
Python Programming – 360DigiTMG
SQL – 360DigiTMG
Power BI – 360DigiTMG

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