Prajyot Mane
Pune
Summary
Data Scientist with expertise in developing machine learning-based fraud detection systems that accurately identify fraudulent credit card transactions from imbalanced datasets. Delivered impactful insights through data analysis and visualization, applying Python and SQL to enhance financial security. Committed to contributing to collaborative, results-oriented teams focused on data-driven decision-making.
Overview
1
1
year of professional experience
3
3
years of post-secondary education
1
1
Certification
Work History
Internship
NEXANOVA PROTECH
07.2025 - 01.2026
Education
PG Diploma in Data science and Analytics -
First Bit Solution
PuneBachelor of Computer Science -
Yashwantrao Chavan Institute of Science
Satara 06.2022 - 05.2025
Skills
- Python
- Machine Learning
- Deep Learning
- NLP
- Statistics
- Data visualization
- Predictive modeling
- Supervised Learning
- Unsupervised Learning
- SQL
- MySQL
- Pandas
- Numpy
- Seaborn
- Matplotlib
- SciKit-Learn
- TensorFlow
- Keras
- NLTK
- Time Series
- Excel
- Github
- Jupyter Notebook
- Data cleaning
- Data Management
- Statistical analysis
- Team collaboration
- Machine learning
- Consumer Behavior Analysis
- Microsoft power BI
Certification
NEXANOVA PROTECH (Internship), Data Analyst, 07/01/25, 01/01/26
Disclaimer
I hereby declare that the above particulars of facts and information stated are true, correct and complete to the best of my belief and knowledge.
Projects
Credit Card Fraud Detection, To build a machine learning-based fraud detection system capable of accurately identifying fraudulent credit card transactions from a highly imbalanced dataset by applying effective sampling techniques and predictive modeling to improve financial security., Collected the data from various sources and selected the relevant features using feature selection methods., Performed the necessary EDA to get the insights., Implemented Logistic Regression and evaluated performance using cross-validation, confusion matrix, and precision-recall metrics., Built and evaluated models like Logistic Regression and Decision Tree, Random Forest achieving 92% accuracy., Output response time less than 1 sec., Pandas, Numpy, Sci-kit learn, Matplotlib, Seaborn, VS Code, Jupyter Notebook, Github, Git, AWS
Languages
English
First Language
Timeline
Internship
NEXANOVA PROTECH
07.2025 - 01.2026
Bachelor of Computer Science -
Yashwantrao Chavan Institute of Science
06.2022 - 05.2025
PG Diploma in Data science and Analytics -
First Bit Solution