Hi, I'm Amaan Vora
and I love to code.
I am a Master’s student in Statistics (Data Science) at Rutgers University, with expertise in Python, R, SQL, and data science technologies.
My professional experience includes roles as a Lead Front-End Developer, Graduate Research Assistant, and Machine Learning Intern at Siemens Limited, where I contributed to projects in website usability, algorithm efficiency, and machine learning model development for business insights.
I am also passionate about current research in computational linguistics and data summarization.
EXPERIENCE
Lead Front-End Developer
Graduate Research Assistant (Statistics Department)
Global Business Services Intern (Machine Learning Division)
Lead Developer / Analyst
(2023 - )
(2023)
(2020)
(2021)
PROJECTS
Abstract Text Summarization Using Generative Adversarial Networks
Key Targets :
Machine Learning, Classification, Neural Networks, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
TFIDF Vectorization, BERT, RoBERTa, SiameseBERT
Programming Language :
Python
Identification and Classification of Conditions owing to Age from ICR dataset
Key Targets :
Supervised Machine Learning, Classification, Statistical Inference, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
Classification Algorithms (scikit_learn), OneHot Encoder, GradientBoost
Programming Language :
Python
Analyzing Customer Demographics and Behavior to Strategize Targeted Marketing for Online Retail
Key Targets :
Clustering, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
tidyverse, ggplot2, dplyr
Programming Language :
R Programming
Generic Recommender System for Formatted Data - Visualization via NetworkX
Key Targets :
Machine Learning, Clustering, Neural Networks, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
K-Means Clustering, Agglomerative Clustering, NetworkX
Programming Language :
Python
Analyzing and Predicting Factors Affecting Credit Approval
Key Targets :
Machine Learning, Regression, Statistical Inference, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
tidyverse, ggplot2, dplyr
Programming Language :
R Programming
Building and Optimizing a Search Application for a Vast Twitter Database
Key Targets :
Machine Learning, Database Management, Sentiment Analysis, Relational Database, Non-relational Database
Key Libraries :
PostGRESQL, MongoDB, Word2Vec
Programming Language :
Python
Analyzing Factors and Forecasting Outcome of the S&P500 Index
Key Targets :
Machine Learning, Classification, Neural Networks, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
tidyverse, ggplot2, dplyr
Programming Language :
R Programming
A Computational Linguistics Approach to Clustering Scientific Research Papers
Key Targets :
Machine Learning, Clustering, Neural Networks, Transformers, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
TFIDF Vectorization, BERT, RoBERTa, SiameseBERT, t-SNE, uMAP, K-Means Clustering
Programming Language :
Python
Analyzing Factors and Predicting the Data Science Job Market
Key Targets :
Machine Learning, Classification, Neural Networks, Data Analysis, Feature Engineering, Data Visualization
Key Libraries :
Classification Algorithms (scikit_learn), SMOTE, Tensorflow & Keras, GBM Classifier
Programming Language :
Python
