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Pratik Bhambri

@pratikbhambri

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Enthusiastic data scientist with expertise in machine learning and analytics.

India

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What I'm looking for

I am looking for opportunities that foster continuous learning and allow me to apply my data science skills to solve complex business challenges.

I am an enthusiastic and detail-oriented data scientist with a strong foundation in Python, machine learning, and statistical analysis. My passion lies in leveraging data to drive actionable insights and solve real-world business problems. I am familiar with key tools such as NumPy, pandas, SQL, and visualization libraries like Matplotlib and Seaborn.

Currently, I had pursued my Master's Diploma in Data Science & AI from Boston Institute of Analytics, where I gained my skills in data-driven decision-making. My previous academic background includes a Master of Arts in Economics from Lovely Professional University which will end in year 2026 and a Bachelor of Arts from the University of Delhi. I have successfully designed and implemented a machine learning-based fraud detection system, achieving an impressive ROC-AUC score of 99.96%.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Spinnaker Analytics

Jan 2025 - Present (5 months)

Currently creating machine learning models using Linear and Logistic Regression, as well as other algorithms like Random Forest, AdaBoost, and XGBoost on financial and sales datasets.

Machine Learning Logistic Regression Random Forest AdaBoost XGBoost Data Analysis Python SQL

Data Scientist

Boston Institute of Analytics

Jul 2024 - Jan 2025 (6 months)

Completed a master's diploma in Data Science and AI, focusing on leveraging data for actionable insights and solving business problems using Python and machine learning techniques.

Python Machine Learning Data Analysis NumPy SQL Matplotlib Statistical Analysis Data Visualization

Data Science Project

Self-Employed

Dec 2022 - Apr 2023 (4 months)

Designed and implemented a machine learning-based fraud detection system, achieving a ROC-AUC score of 99.96%. Developed advanced feature engineering strategies for imbalanced datasets.

Fraud Detection Logistic Regression Gradient Boosting SMOTE Data Strategy Python

Customer Segmentation Project

Self-Employed

Dec 2022 - Apr 2023 (4 months)

Developed unsupervised learning models for customer segmentation using K-Means and Agglomerative Clustering, along with dimensionality reduction techniques for visualization.

Customer Segmentation Unsupervised Learning Models K Means T SNE Data Visualization Python

Education

Degrees, certifications, and relevant coursework

Lovely Professional University

Master of Arts in Economics, Data Science

2024 - 2026

Passionate about data-driven decision-making and continuous learning in the field of data science.

Boston Institute of Analytics

Masters Diploma in Data Science, Data Science

2024 - 2024

Enthusiastic and detail-oriented data scientist with a strong foundation in Python, machine learning, and statistical analysis. Adept at leveraging data to drive actionable insights and solve real-world business problems.