ABHISHEK TIBREWAL

linkedin.com/in/aabhishektibrewal 201-***-**** adcg26@r.postjobfree.com tibrewal.mystrikingly.com SUMMARY Motivated Engineer trained in academics (Data Science and Computer Science) and leadership. An insatiable intellectual curiosity; able to mine insights located within large sets of structured, semi- structured and unstructured data. Well-versed in data and quantitative analytics, statistics and machine learning. Proven skills in project management. Kaggle: https://www.kaggle.com/abhishektibrewal SKILLS Python, R, SQL, NoSQL (MongoDB), SAS, SPSS, Talend, Matlab, Tableau, Statistical Analysis Experimental Design, Predictive Modeling, Watson APIs, Microsoft Excel, ETL, JIRA, Cognitive Computing, Windows/Linux Flavor (Ubuntu, Debian), Confluence https://github.com/abhishek-tibrewal

EDUCATION Stevens Institute of Technology, Hoboken, NJ August 2016 – December 2017 M.S (Master of Science) in Computer Science Cumulative GPA: 3.772 Coursework include: Natural Language Processing, Data Mining (Multivariate Analysis, Machine Learning Algorithms, Inferential Statistics), Cloud Computing, Web Analytics Amity University, Noida, India August 2012 – April 2016 B. Tech (Bachelors of Technology in Computer Science Engineering) EXPERIENCE Data Scientist, Marsh & McLennan Companies April 2018 – Current

Build an NLP Model on Multi-Class Classification problem which redirect the service desk tickets (Data Center Operations) to the specified group based on description hence removing a lot of manual work, resulting in faster and more accurate resolve time of the tickets

Conduct statistical analysis on data to ensure correct predictive forecasting or classification using R and Python

Automate several processes by pulling data from different sources, transforming, mapping by using Talend, R and MongoDB hence removing chances of human errors

Maintain all aspects of end-to-end data processing utilizing analytical systems, data repositories and verifies the accuracy of the data and acts as a liaison with data owners

Collaborate in the efforts of designing and maintaining the Data Lake (single source of truth) Data Scientist Intern, IBM June 2017 – August 2017

Created an automated model by analyzing unstructured data using several techniques of Natural Language Processing, machine learning algorithms such as LDA, K-means for clustering, scripted model in Python

Designed a Chat Bot using Watson Conversation Service; Completed several certificates and badges on Watson APIs and Data Science; practiced agile methodologies regularly Data Analyst Intern, Actiknow Business Consulting May 2015 – June 2015

Gathered and documenting requirements from clients; Developed Tableau reports to provide clear visualizations of various industry-specific Key Performance Indicators (KPIs) PROJECTS Predicting crimes in Chicago from Weather (Using Python) December 2017 Investigated the relationship between weather and crime rate; the effect of weather on crime can be a valuable addition enabling law enforcement agencies to stop crimes better and faster; concluded that

“episodes of extreme climate make people more violent toward one another” Predicting Boston Housing Prices (Using SAS) April 2017 Developed a model which can precisely predict housing prices; Used PCA to deal with correlation between variables and then implemented Multiple Regression; model can be used by real estate agents or customers to predict the correct price of houses with an accuracy of 83% Predictive Analytics for Employees Attrition (Using R, SPSS and Watson Analytics) April 2017 Developed model using R & SPSS modeler; applied classification techniques such as Decision Trees

(CART, Random Forest); used Watson Analytics for Exploratory Data Analysis (Descriptive Statistics); Using this model, HR department of any company can minimize attrition by improving retention strategies and save over $5 million per year by just retaining 10% of employees LEADERSHIP Treasurer: Society of Computer Science (SOCS), Stevens Institute of Technology