AKSHAY KAPOOR

ac8azv@r.postjobfree.com 617-***-**** http://www.linkedin.com/in/akshaykapoor347 https://akshaykapoor347.github.io/ https://github.com/akshaykapoor347 Boston

EDUCATION

Northeastern University, Boston, MA March 2019

Master of Science in Analytics, GPA 3.8. Courses in probability and statistics, big data and data management, predictive analytics, data mining, communication and visualization of data, linear programming, GIS.

Xavier Institute of Engineering, Mumbai, India May 2015

Bachelor of Engineering in Computer Engineering, GPA 3.4. Courses in Data structure and algorithm, Discrete mathematics, computer networks, database management system.

SKILLS & TECHNOLOGIES

Programming Languages: R, Python (Pandas, Scikit-learn, NumPy, Seaborn, Matplotlib, Flask), MATLAB, C#.

Software: Tableau, Excel, Power BI, ArcGIS, Google Analytics, Git.

Machine Learning: Regression, Classification, Time Series Analysis, Clustering, Neural networks, NLP.

Statistical Methods: Descriptive statistics, hypothesis testing, ANOVA, A/B Testing, Bayesian statistics.

Big Data and Databases: Hadoop, AWS EC2, PySpark, Oracle SQL, MySQL, Access, Google Cloud.

WORK EXPERIENCE

DTonomy: Data Science Intern Jan 2019 – Apr 2019

Created and deployed a product for email security utilizing machine learning and Natural language Processing.

Extended product features of AI assisted alert management platform and tested existing APIs.

Researched techniques for detection of suspicious and malicious URL using machine learning.

Northeastern University: Graduate Teaching Assistant for intermediate analytics Sept 2018 – Mar 2019

Mentored students through office hours and one-on-one communication. Prepared lessons according to course outline to convey all required material and deepen student understanding of subject matter.

Infosys: Data analyst Apr 2016 – July 2017

Analyzed trends and developed a product recommendation system that helped in increasing sales by 10%.

Designed and presented trends in data using Tableau and provided product recommendation strategies.

Performed data mining activities using Python, R and Excel such as data collection, data cleaning, data validation, feature engineering, data modeling and visualization.

Predicted potential geographic locations for the client to open new stores in US and Canada.

Collaborated with team to understand the KPI and make strategic business decisions.

Infosys: Test Engineer Nov 2015 – Mar 2016

Automated test scripts for employee background verification portal using Selenium.

PROJECTS

Sentiment Analysis on IMDb reviews

Performed web scraping using beautiful soup on IMDb reviews of a TV series and explored, wrangled, analyzed the reviews; classified the reviews as positive and negative using TextBlob and generated word cloud for reviews.

Build a Multinomial Naïve Bayes algorithm and achieved 81% accuracy using Synthetic Minority Over-sampling.

Customer Targeting for Viacom

Performed customer segmentation and profiling using clustering on demographic data and cpm estimates. Build customer profiles based on demographics to enable better guaranteed contracts.

Advanced House Price Prediction

Implemented regression analysis on a large dimensional dataset; Performed imputation, feature engineering and created a pipeline using advanced regression techniques like ElasticNet, XGBoost, LightGBM; Top 14% score on active Kaggle competition.

Image Recognition using Convolution Neural Networks

Implemented image recognition using deep learning libraries such as TensorFlow, Theano, and keras to classify from a dataset consisting of 25000 images of dogs, cats and achieved 84% accuracy.

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