Data Analyst Python
Resume:
RISHIKA KAPOOR
DATA SCIENCE & ANALYTICS
CONTACT
add7ik@r.postjobfree.com
Cincinnati, OH
rishikakapoor.com
linkedin/rishikakapoor
github/rishikakapoor
medium/rishikakapoor
PROFILE
Data scientist who relies on data mining and
predictive data analytics to yield insights that
drive intelligent strategies and empower
business teams, resulting in top line growth!
EDUCATION
UNIVERSITY OF CINCINNATI [CINCINNATI, OH]
Master of Information Technology
Data Science Concentration
RAJIV GANDHI UNIVERSITY [INDIA]
Bachelor of Computer Science
TECHNICAL SKILLS
Python (pandas, NumPy, Matplotlib,
Seaborn, Scikit-learn, TensorFlow,
Keras, NLTK, XGBoost, PySpark)
R (DBI, dplyr, ggplot2, xlsx)
Database: MySQL
Natural Language Processing, Deep
Learning, Machine Learning
(Regression, Classification,
Clustering,)
Data Visualization- Tableau, ggplot2,
Crystal Reports
Advanced Analytics
Statistics and Probability
MANAGEMENT SKILLS
Agile and Scrum Methodology
Problem Solving, Presentations
JIRA
EXPERIENCE
March 2020 - PRESENT
Data Scientist Upwork-Freelancer
Engineered 10+ new features to forecast the monthly payment amount for the next 6 months for 200K accounts and used Logistic Regression to predict the respective month’s payment probability. Tested the model using mean square error and accuracy score.
Helped client scraping the data from IMDB website, aggregated data, clean it and reform it into a csv file. Implemented Random forest to predict the movie ratings. Interesting Finding: Movie duration is one of the important features in determining movie ratings.
AUGUST 2018 - PRESENT
Data Analyst IT@UC
Working on automation, validation and forecasting to design a content- based recommendation system for university students which will provide students with targeted services and activities over the campus enhancing customer experience and saving excess navigation time. The model is designed on Python using TF-IDF algorithm.
upheld, and promote University events. Powered by analysis using Tableau, this increased the University website views rate by 10%. Working directly on complex database systems to analyze, clean and transform data into stored procedures that are used in the application development.
PROJECTS
Developed and deployed a salary prediction application which business' HR and talent functions can use to optimize their compensation strategy, acquire the best talent and improve retention rate in competitive labor markets. This application was developed in Python, relies on Random Forest Regression Model, was trained on 150 MB data set with 9 features and achieved .301 MSE.
Build NLP pipeline for restaurant dataset which e-commerce platforms can use to estimate customer retention rates, and sales conversion strategies can be optimized to increase customer satisfaction rates. This application was built in Python, relies on Naive Bayes Classifier, was trained 100 MB data set and achieved 90% accuracy.
Developed a house price prediction application which real estate investors can use analyze market in real time. This application was developed in Python, performed advanced regression technique and the Gradient Boosting Regressor Model was selected by comparing MSE, was trained on 120 MB dataset with 80 features and achieved 88% accuracy.
Contact this candidate