Data Scientist

• Jul 2019 - Present

Tutor

• Jan 2019 - May 2019

• Effectively educated Data Visualisation techniques in Tableau and Power BI, extracting data from websites using Rvest library from Rstudio and Data cleaning process in R using dplyr, tidyr and stringr libraries. • Explained the concepts of SQL databases and to build SQL queries in Azure Data Studio. • Explained the concepts of Text Analytics, Sentiment Analytics, and Emotional Analytics in R using the libraries qdap, tm, text2vec, Rweka, sentimentr, lexicon, wordcloud and radarchart. Show less

Data Science Consultant

• Nov 2018 - May 2019

• Analyzed sensor data from a sensing device called Scout which records pressure, humidity, latitude, longitude, wind direction, wind speed to find the best routes to drive by in Boston, MA. • Contributed to clean the data using filters as advised by company personnel, analyzed the data to find outliers and anomalies in python from the recorded data. • Distinguish between the wind gust and wind from traffic using data manipulation techniques and analyzing techniques from the recorded data. • Contributing to predict the wind speed on roads and best routes using machine learning algorithms which save millions of dollars to Uber cabs and maximize the profits to AvantCourse Company. Show less

Data Science Consultant

• Nov 2018 - May 2019

• Accessed sensor data which records Anomalies, analyzed sensor data and use data manipulation techniques to get the required data from JSON files in python using Pandas and json dependencies. • Participate in pulling data from MySQL Workbench, data cleaning and preprocessing, Building Machine learning Algorithms and to interpret the results. • Building Machine learning algorithms to decrease sensing Non-Smoking events and also to reduce human intervention which reduces 10% of FreshAir sensors of their total investments. • Apply machine learning techniques to increase the accuracy of machine learning models like RandomForest, Neural Networks, Gradient Boosting, XG boost by at least 2%. • Contributing to an increase in the response time of sensors to detect smoking events with machine learning algorithms from 15 minutes to 10 -14 minutes. Show less

Graduate Student in Analytics and Data Science

• May 2018 - May 2019

Coursework in: • Probability • Inferential statistics • Statistical models • Relational databases(SQL) • Linear algebra • Collecting data through APIs and web scraping • Supervised and unsupervised machine learning • Predictive modeling using multiple linear regression, logistic regression, K-nearest neighbors (KNN), and Naive Bayes • Data clustering (K-means, DBSCAN) • Dimensionality reduction (PCA, PLS, tSNE) • Regularization methods (Lasso, Ridge, Elastic Net) • Tree-based models (CART, bagging, random forest, boosted trees) • Boosting methods (Ada, Gradient, XGBoost) • Neural Networks • Natural Language Processing (bag of words, word clouds, sentiment analysis, emotion analysis, Word2Vec) • Computer vision (object detection, image classification via Mask R-CNN) • Time series data analysis Strengthening skills in: • Data extraction from a variety of sources • Data cleaning • Data management • Text mining Software, programming languages, and platforms: • Python (pandas, NumPy, Keras, scikit-learn, matplotlib, Seaborn) • R (dplyr, ggplot2, plotly, stringr, lubridate, Shiny, markdown, tidyr, qdap, sentimentr, word cloud, radar chart) • Tableau and Tableau Prep • Microsoft Power BI • Shiny web application • Dash • Bokeh • JMP statistical software • SQL Show less