NISARG BHATT

Boston, MA adkd9w@r.postjobfree.com 857-***-**** linkedin.com/in/nisargbhatt98 github.com/Grasin98 EDUCATION

Northeastern University, Boston Sept 2019 - May 2021 Master of Professional Studies in Analytics

• Coursework: Introduction to Analytics, Probability Theory and Introduction to Statistics, Database Management Systems, Communication and Visualization, Enterprise Analytics, Predictive Analytics, Data Mining LNM Institute of Information Technology, India Aug 2015 - Jun 2019 Bachelor of Technology in Mechanical-Mechatronics Engineering

• Coursework: Mechanical Engineering, Robotics & Industrial Automation, Microprocessors, Mechatronics System Interface. SKILLS

Programming Languages and Database: Python, R, Java, C, MySQL, SQL Server, Oracle Business Intelligence: Tableau, R Shiny, PowerBI, MS Excel Machine Learning Algorithms: Regression (Linear and Logistic), Decision Tree, Random Forest, SVM, KNN, PCA, Forecasting, ANN, CNN, RNN, LSTM, XgBoost

Tools and Frameworks: AWS, Azure, R-Studio, OpenCV, PyCharm, Jupyter Notebook, MATLAB, Keras, Tensorflow, Flask, Microsoft Excel, RapidMiner, Microsoft Office WORK EXPERIENCE

Zyprr, Boston,MA Sept 2020 - Current

People Data Science Coop – Python, SQL, Tableau

• Created a SQL database to store customer data and developed strategy to analyze customer behavior based on relationship score, percentage of video watched, plays, likes and various other features from developed KPIs.

• Built 3 highly interactive and actionable reporting tool for videos, campaigns and trends with broad visibility to differentiate potential customer, identified areas of improvement in reporting tool, relationship score algorithm, and internal processes.

• Created and optimized candidate marketing campaigns across multiple channels. Northeastern University, Boston, MA Aug 2020 - Current Graduate Research Assistant– Python

• Developed financial stress measure and risk model by calculating the sentiments using NLP and machine learning techniques, analyzed large volume of financial textual content and various other non-financial data.

• Implemented predictive and prescriptive algorithms using Bag of words, Tf-idf and Bi-directional Encoder Representations from Transformers (BERT).

• Worked with Joint Research Centre (JRC) to publish research paper in top academic journals. Fusion Informatics Ltd., Ahmedabad, India Jan 2019 - May 2019 Data Analyst Intern – R, Tableau

• Developed KPIs responsible for vehicle sales, engineered features as part of data explanatory analysis.

• Devised 2 interactive Tableau dashboards indicating KPIs of 1500 vehicle sales, monitored sale patterns.

• Predicted vehicle sales using selected KPI’s by applying various models, generated insights and opinions to make key decisions. Reliance Industries Ltd., Mumbai, India May 2018 - July 2018 Data Science Intern – Python, Tableau

• Collected news articles of competing companies from Bloomberg, sorted according to weight of importance matrix.

• Performed sentiment analysis of articles based on internal features and provided sentiment scores between -1 and 1 to each article, analyzed how news of competing companies affects current trade of Reliance.

• Developed Tableau interactive dashboard obtaining insights about change in sentiment score monthly, quarterly and yearly. PROJECTS

Coronavirus Data Visualization- Python, Tableau, GCP July 2020

• Gathered data from publicly available from WHO, CDC using Tableau Server for dates 31 Jan’20 to 9 Feb’20, performed inferential statistics for top 10 countries/provinces in China affected by coronavirus using correlation.

• Calculated Fatality ratio and recovered vs confirmed ratio for mainland china, plotted infected areas with heat map and compared deaths of previous corona-virus outbreaks with NCoronavirus and visualized using pie charts.

• Parsed through a large anonymized Kaggle dataset with 200 feature numerical variables to analyze probability of specific transaction on product/service by customer in future.

• Explored statistical distribution of features and applied PCA to extract features and reduce dimensionality of data and devised a solution to predict transaction using XgBoost model with performance accuracy of 87.9% on validation set. ACHIEVEMENTS AND CERTIFICATIONS

• Won NASA Space App Challenge 2019; Global Nominees. Top 250 out of 29,000 teams worldwide. Oct 2019

• Deep Learning.ai specialization certification; Coursera – Andrew Ng. May 2018

• Machine Learning A-Z, Advanced Tableau, Intro to Power BI, Probability and Statistics - Udemy Aug 2017 Santander Customer Transaction Prediction- Python, AWS Sept 2019

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