RAHUL JAISWAL

Well-qualified Data Scientist experienced working with vast data sets to break down information, gather relevant points and solve advanced business problems. Skilled in predictive modeling, data mining and hypothetical testing. Offering 5+ years of experience in improving business operations.

• Outlier Detection technique(Z-score, OLAP score, Break-point -analysis
• Performance Analysis using AUC
• Data Scientist
• HCL(Permanent)
• Citi Bank(Compliance and Risk Management)
• Project : Fraud Detection
• Nov 2018 - Jan 2020
• Fraud is as old as humanity itself and can take an unlimited variety ofdifferent forms
• Moreover, the development of new technologies providesadditional ways in which criminals may commit.The use of credit cards isprevalent in modern day society and credit card fraud has kept on
• Responsibilities
• Communicated and coordinated with the respective departments tocollect business requirement
• Data Mining, Data Cleaning, EDA, Hypothesis Testing
• Tools used - Python, AWS, RDBMS, NOSQL
• Under sampling methods is used to balance the class distribution in thetraining setbeamjobs.com
• Used Recursive ensemble approach (REA) to imbalanced learning problemin training data chunk
• Models Build - Unsupervised Techniques - PCA, K-MEAN(clustering)
• Implemented machine learning model like logistic regression, CART and
• Random Forest
• Detecting Anomalies
• Outlier Detection technique(Z-score, OLAP score, Break-point -analysis
• Used GBM with learning to rank approach
• Used SpacyNER for country name and person name detection
• Performance Analysis using AUC
• Data Scientist
• Capgemini Pvt Ltd(Permanent)
• General Electric Insurance(Contingent)
• Project :Insurance Claim Prediction Using Machine Learning

Azure Fundamental