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Priyanka Wangde

Priyanka Wangde

Data Scientist

Mumbai
80
Profile Score

About

Data Scientist with close to 3+ years of experience in machine learning, predictive analytics, and data analysis within banking and insurance sectors. Proficient in Python and SQL with strong knowledge of exploratory data analysis, statistical techniques, and Scikit-learn for building fraud detection and risk prediction models. Skilled in feature engineering, model tuning, and managing imbalanced datasets to deliver business-focused data solutions.

Skills & Expertise (28)

Python Advanced
8.3/10
3
Years Exp
scikit-learn Advanced
8.1/10
3
Years Exp
Predictive Modeling Advanced
8.0/10
3
Years Exp
ROC-AUC MLOps Model Monitoring Model Deployment ETL Pipelines Plotly Seaborn Matplotlib MongoDb MySql Model validation Cross-Validation Precision–Recall F1-Score Data Preprocessing Feature Engineering Statistical Analysis Exploratory data analysis XGBoost Random Forest Regression Classification NumPy Pandas SQL

Work Experience

Junior Data Scientist

RBL Bank

May 2024 - Mar 2025

Cleaned and transformed large-scale banking transaction and customer datasets using Pandas, NumPy, and SQL for machine learning pipelines. Conducted exploratory data analysis to identify transaction trends and customer behavior patterns for risk modeling. Built and validated regression and classification models with automated ETL preprocessing. Improved model accuracy by 15–20% through feature engineering and hyperparameter optimization. Prepared models for deployment and performance monitoring in production environments.

Data Scientist

LTI Mindtree

Mar 2025 - Present

Developed machine learning models using Python and Scikit-learn to detect fraudulent insurance claims from customer, policy, and claim datasets. Performed data cleaning, preprocessing, exploratory data analysis, and feature engineering to improve fraud detection accuracy. Handled imbalanced datasets using SMOTE and class weighting; trained and validated Logistic Regression, Decision Trees, Random Forest, and XGBoost models. Evaluated model performance using precision–recall curves, F1-score, and ROC-AUC, improving fraud detection recall and reducing false positives. Identified key fraud indicators that accelerated claim processing and supported risk-based decision making. Supported model deployment through batch prediction pipelines and monitored model performance.

API/UPI Implementation Test Manager

Harjai Computers Pvt. Ltd.

Jun 2022 - May 2024

Tested payment gateway and UPI APIs for banking applications using Postman and SoapUI. Designed test cases, tracked defects, and analyzed transaction logs to identify payment failures and system issues. Supported UAT and production deployments to ensure transaction reliability and system stability. Collaborated with development teams to resolve API performance and transaction processing issues.

Education

MBA (Artificial Intelligence & Machine Learning) - D. Y. Patil University

- · Afghanistan

Bachelor of Engineering (Electronics & Telecommunication) - Shivaji University

- 2020 · Afghanistan

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Profile Score Breakdown

📷 Photo 10/10
📄 Resume 10/10
💼 Job Title 10/10
✍️ Bio 10/10
🛠️ Skills 20/20
🎓 Education 10/10
⏱️ Experience 5/15
💰 Rate 0/5
🏆 Certs 0/5
Verified 5/5
Total Score 80/100

Profile Overview

Member sinceMar 2026

Skills (28)

Python scikit-learn Predictive Modeling ROC-AUC MLOps Model Monitoring Model Deployment ETL Pipelines Plotly Seaborn +18 more