Neetu Singh

www.linkedin.com/in/neetu-singh Boston, MA 857-***-**** ac33pm@r.postjobfree.com

EDUCATION

Northeastern University, Boston, MA (GPA-3.78) May 2018

Master of Science with major focus on Data Science

Rajasthan Technical University, India (GPA-3.62) Apr 2012

Bachelor of Technology in Computer Science

SKILLS

Data Science:

Logistic regression, Linear regression, SVM, Decision trees, Naïve Bayes, PCA, Neural Network, Spark, Pandas, scikit-learn, Matplotlib, Numpy, Scipy, Stanford NLP, ARIMA, RShiny, Tensorflow

Programming Languages:

Python, R, Java, SQL, Neo4j

Big Data Tools:

Hadoop, Oozie, Hive, HBase, MongoDB

BI Tools:

Cloud Computing

Power BI, Tableau, SAP BW/BI

Microsoft Azure, AWS(EC2, S3)

PROFESSIONAL EXPERIENCE

Ahold Delhaize Jun 2016-Dec 2016

Data Scientist

•Built a Personalized product recommendation system to suggest products based on customer’s purchasing history using Train Matchbox algorithm in Microsoft Azure Machine Learning Studio

•Developed a recipe recommendation system using Neo4j graph DB in which customers are recommended Recipes based on the ahold products in their shopping cart

•Extracted Ahold tweets and Facebook posts and did sentiment analysis on it to help marketing teams to analyze the data and help customers

•Analyzed the promotional data for a particular list of products to forecast.

•Implemented an autoregressive integrated moving average (ARIMA) model to do time series forecasting for next 30 days

IBM –International Business Machine Apr 2014- Aug 2016

SAP-Business Intelligence Consultant

•Performed analysis, development and Implementation of standard / customized Info Cubes and Data Store Objects for business end-users in the application areas of Sales and distribution, SRM, Finance-Clarity, MM using SAP BI7.0

•Designed and developed several web reports using web templates in Web Application Designer, BEx Suite (BEx Query Designer, Web Application Designer, Analyzer)

•Resolved application issues thereby improving customer satisfaction by 20%

Clients: ERICSSON and Schlumberger

PROJECTS Kaggle Data Science Competitions

Prudential Life Insurance Risk Predictions: Jan 2017- Mar 2017

•Built a Support Vector Machine (SVM) based classifier to categorize almost 60,000 Life Insurance applicants for Prudential Insurance into various Risk categories, aiding in the process of buying life insurance. Tuned the performance of the models to achieve best prediction (95% accuracy)

Titanic: Machine Learning from Disaster Jan 2017 - Feb 2017

•Prediction of the fate of the passengers who boarded the titanic, which sank in the Atlantic Ocean

•Applied Regression tree algorithm to predict the variables

•Results indicate that the predictors sex/title, fare price, age, and passenger class are the most important variables in predicting survival of the passengers

Statistical Analysis of Response Ware Software Sept 2016 - Dec 2016

•Conducted it on the sample means of the number of errors and tested the hypothesis test whether there is an increase or decrease in the number of errors throughout the semester after using the Software

•Developed visualization using Tableau, and conducted statistical analysis using Minitab and MS Excel

Kickstarter.com Data Collection, Storing, Retrieving Feb 2017- Mar 2017

•Scraped the category based successful and unsuccessful projects using R and stored the data in mongo db.

•Did various data analysis like checking the section of projects which deadlines are about to pass etc and visualized the statistical data in tableau

•Predicted the most successfully backed projects and less backed or failed projects for 5years

Contact this candidate