
Software Engineer at Genpact . Alumni of National Institute of Technology, Jamshedpur (2019-2022).
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Genpact
Data Scientist
June 21, 2026 – Present
clinexa-hospital-management
June 4, 2026 – Present
Clinexa A smart Hospital Management System - A full-stack web application for managing doctors, receptionists, departments, appointments, and hospital operations.
View ProjectShubham-Portfolio
January 29, 2024 – January 29, 2024
Shubham-Portfolio — GitHub repository
View Projectjava-advance-HandsOn
February 28, 2022 – March 4, 2022
java-advance-HandsOn — GitHub repository
View ProjectBank-Marketing-Prediction-Linear-Regression----RFE-VIF-STATE-
February 20, 2021 – February 20, 2021
Bank-Marketing-Prediction-Linear-Regression----RFE-VIF-STATE- — GitHub repository
View Project-Car-Price-Prediction-Linear-Regression---RFE-
February 20, 2021 – February 22, 2021
-Car-Price-Prediction-Linear-Regression---RFE- — GitHub repository
View ProjectLinear-Regression-Model-in-Machine-Learning
January 10, 2021 – January 10, 2021
Linear regression is one of the easiest and most popular Machine Learning algorithms. It is a statistical method that is used for predictive analysis. Linear regression makes predictions for continuous/real or numeric variables such as sales, salary, age, product price, etc. Linear regression algorithm shows a linear relationship between a dependent (y) and one or more independent (y) variables, hence called as linear regression. Since linear regression shows the linear relationship, which means it finds how the value of the dependent variable is changing according to the value of the independent variable. The linear regression model provides a sloped straight line representing the relationship between the variables. Consider the below image: Linear Regression in Machine Learning Mathematically, we can represent a linear regression as: y= a0+a1x+ ε Here, Y= Dependent Variable (Target Variable) X= Independent Variable (predictor Variable) a0= intercept of the line (Gives an additional d
View Projectmail_spam_using_naive_bayes
January 10, 2021 – January 10, 2021
Naïve Bayes model , this is a machine leaning model
View ProjectCultural Fit Analysis
The candidate's projects show a mix of data science and full-stack development, indicating a diverse interest. The target role is Data Scientist, and several projects align with this. However, the 'experienceLevel' is 0, which contradicts the listed 'Data Scientist' role at Genpact starting in 2026, suggesting potential data inconsistency or a future role. The breadth of skills (Java, JavaScript, HTML, CSS, TypeScript, Jupyter Notebook) suggests adaptability, but the depth in specific data science tools beyond basic regression models is not clearly demonstrated.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.