Arjun Vohra

Recent graduate with a strong foundation in Data Science and Machine Learning Engineering, equipped with hands-on experience in statistical analysis, predictive modeling, and data-driven decision-making. Proficient in Python programming languages with a solid understanding of machine learning algorithms, data preprocessing, and model evaluation. Adept at using tools and libraries like scikit-learn and Pandas for developing and deploying machine learning models.

Project -1

Food Hub Data Analysis 

The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to get a fair idea about the demand of different restaurants which will help them in enhancing their customer experience. Perform the data analysis to find answers to these questions that will help the company improve the business.

Project-2 

Moisture Content Analysis for ABC Asphalt Shingles
Conducted hypothesis tests to verify if the mean moisture content in shingles is within permissible limits and compared the means of two different types (A and B) using statistical analysis. Determined whether both types meet the company's quality standards.

Project-3

State-wise Health and Income Clustering
Performed clustering analysis on the State wise Health income dataset to group states based on health and economic conditions. The clusters provide insights to the government for taking targeted measures to improve the health and economic outcomes of the states.

Project-4

Firm Sales Prediction for Investment Firm
Developed a linear regression model to predict the sales of 759 firms using firm-level data. Identified the top 5 most important attributes to assist the firm in making informed investment decisions.

Project-5

Predicting Car Crash Survival and Key Factors Analysis
Developed logistic regression and random forest model to predict the likelihood of survival in car crashes. Analyzed important factors affecting survival to provide insights for the government to enhance vehicle safety regulations.

Project-6

Employee Transport Preference Prediction

Built and evaluated various machine learning models to predict ABC Consulting employees preferred mode of transport based on factors such as age, salary, and work experience. Selected the best-performing model to provide accurate predictions for employee commute options.

Project-7

Predictive Tool for Financial Health Assessment
Created a machine learning model to predict company default risk over the next two quarters by analyzing historical financial metrics. The tool aims to evaluate debt management and credit risk, assisting businesses and investors in making informed financial decisions and managing risk effectively.

Project -8

HR Salary Prediction
The goal of the HR department at Delta Ltd. is to ensure that employees with similar profiles receive consistent and fair compensation. To eliminate discrimination and minimize human judgment in determining the salaries to be offered.

Performed Exploratory data analysis for all the features using various plots.

Data cleaning ie Missing or null values to be addressed,outlier treatment as well as scaling and encoding the continuous and categorical variables respectively using data pre processing techniques.

Model Building 

Developed various regression models that predicts the expected salary for candidates to be offered based on various factors such as current salary, experience, education etc.

Model validation and Interpretation

Evaluate the performance and compare multiple models.

Features importance  visualization

Provided the insights and recommendations for fair compensation