Dhanashri Jadhav

Aspiring Data Scientist

Aspiring Data Scientist with 2+ years of experience in data analysis and data modelling. Skilled in Data Analytics, Machine Learning Algorithms, Statistics, Problem solving, and Web & Database Programming. Currently seeking internship in the field of Data Science.

adegzd@r.postjobfree.com

+1-857-***-****

Boston, United States

https://www.slideshare.net/DhanashriJadhav5

linkedin.com/in/dhanashrij

https://github.com/Dhanashrij11

EDUCATION

09/2019 – Present

M.S in Analytics

Northeastern University

Boston, USA

Big Data Predictive Analytics

Artificial Intelligence Machine Learning

Data Visualisation Statistical Analysis

07/2011 – 05/2015

B. E in Information Technology

Gujarat Technological University

Gujarat, India

WORK EXPERIENCE

08/2016 – 06/2019

Data Analyst

E-tech Global Services

Vadodara, India

Led team of enthusiastic and new Data Analysts

Supported the Knowledge Discovery process using the Data Mining Tools

Performed ETL using Python, Pandas, Matplotlib, and Jupyter Notebook

Analyzed client/customer datasets to provide strategic directions to the company using Data Analytics

Performed various statistical analysis using Excel

(VLOOKUP, PivotTable, Charts, VBA, Macro and

Regression Analysis)

07/2014 – 05/2015

IT intern

L&T Technology Services

Vadodara, India

Developed Web App for managing company assets

(HVACS, Elevators, PC’s, Security Access Machines, Vending Machines, and more) in ASP.Net and MySQL

Created an emergency alert system, used to convey

messages to the management in case of critical

condition/failure of the assets.

The application also provided predictive maintenance reports, thereby reducing failures and increasing

efficiency of assets by up to 8%

SKILLS

Python R Tableau PowerBI SQL Pandas

Matlab ETL AWS Keras Scikit TensorFlow

Regression Data Mining A/B Testing Git SAS

EDA Neural Networks Machine Learning Spark

Time Series Scala Deep Learning Google Analytic

ACADEMIC PROJECTS

Superstore Sales Prediction Analysis R Studio, Machine Learning

Performed data profiling, cleaning and linear regression to identify the predictor variables

Analyzed the data (EDA) and implemented XGBoost and Random Forest algorithm for identifying correlation and significant variables Developed generalised linear model and predicted the Superstore's Sales and Profit that could serve as insights to stakeholders Music Recommender System Python, Jupyter Notebook Used subset of “Million Song Dataset’ to create recommendations using Machine Learning Library (MLlib), and Pandas

Created Popularity -based and Personalized Recommender System FIFA Player 2020 Best Team Position Prediction R

Studio,KNN, Naïve Bayes, Random Forest, CNN, Linear Regression

Developed predictive models to predict the team position for the player based on their skills and characteristics

Identified the strongest positive correlation between the position of team and predictor variables

Performed EDA, Linear Regression, KNN Classification, Naïve Bayes, Random Forest, and Neural Networks, achieving accuracy of ~ 80% Fashion MNIST Image Classification R Studio, Kera’s, TensorFlow, CNN

Performed multi-class classification on 70,000 images distributed under 9 fashion labels categorized as Top, Shoes, Bag etc. Performed EDA, KNN Classification, Naïve Bayes, Random Forest, and Neural Networks, achieving accuracy of ~ 90%

Boston Property Assessment 2020 Python, Seaborn, Matplotlib, Sklearn, Spyder

Performed ETL, EDA, removed outliers using skewness-kurtosis, correlations, and heatmap, and extracted most dominant features from dataset of ~175K rows

Developed models to predict the key factors in assessing the land value of Boston using Linear Regression, Lasso Regression, and Ordinary LeastSquare that yielded the adjusted R2 as 90%

Courses

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Achievements/Tasks

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