NISARG BHATT

Boston, MA adem1p@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

Data Analytics Data Warehousing Machine Learning Data Mining Database Modelling Data Visualization Data Wrangling Data Integration Predictive Modelling Statistics Time Series Forecasting Sentiment Analysis Deep Learning Programming Languages and Database: Python, R, Java, C, MySQL, SQL Server, Oracle Business Intelligence: Tableau, R Shiny, MS PowerBI, MS Excel Data Mining Tools: Orange, Weka

Machine Learning Algorithms: Regression (Linear and Logistic), Decision Tree, Random Forest, SVM, KNN, PCA, Forecasting, ANN, CNN, RNN, LSTM, XgBoost

Design and Simulation Software: NetBeans, Eclipse, R Studio, Jupiter Notebook, Anaconda, SQL Server Studio Tools and Frameworks: R-Studio, R Shiny, PowerBI, PyCharm, Jupyter Notebook, MATLAB, Keras, Tensorflow, Flask, Microsoft Excel, RapidMiner, Microsoft Office WORK EXPERIENCE

Fusion Informatics Ltd., Ahmedabad, India Jan 2018 - Apr 2018 Data Analyst Intern – Python, 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 regression models with accuracy of 83.3% against actual trend. Reliance Industries Ltd., Mumbai, India May 2017 - July 2017 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

Santander Customer Transaction Prediction- R Sept 2019

• 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. Live Stream Facial Emotion Recognition - Python Dec 2018

• Constructed a Deep Convolutional Net and used Haar Cascade classifier for classifying facial emotions.

• Classified 4 expressions (Angry, Happy, Sad and Surprise) with an accuracy of 57% on training and 62% on validation set. Statoil/C-CORE Iceberg Classifier – Python May 2018

• Wrangled and pre-processed satellite image data to classify ships and icebergs and trained Convolutional Nets on images to classify sensed target from satellite as ship or iceberg with performance accuracy of 67.3%.

• Evaluated images based on angle of incidence from which image was taken, vertical and horizontal polarization produced from radar backscatter at particular incident angle. Stock Data Analysis – Python, Excel, Tableau Jan 2018

• Collected data of Google stock price ranging from Jan-2016 to Dec 2016 from NASDAQ, visualized trend using Tableau.

• Implemented Simple RNN and LSTM models to predict lowest and highest stock value for a given day for 2017, accuracy metrics was used to compare model performances.

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

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