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Data Scientist

Seattle, Washington, United States
September 10, 2018

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Phone: 206-***-****

***** ** **** **, ********, WA, 98005


Professional Summary

A data enthusiast who loves to harness the power of data with the help of analytics and machine learning and gain meaningful insights to make key business decisions. Education

M.S in Business Analytics, University of Washington Sep '17 - June '18 GPA:3.88/4 B.Tech in Computer Science, Banasthali University, India Jul '07 - May '11 GPA:3.76/4 Experience

Data Science Intern, The Clorox Company (R, Tableau, Text Mining, Google Cloud) Jul 2018 – Present Developing a cloud-based consumer review analytics solution to turn online review data into insights by applying text analytics techniques like topic modelling, part of speech tagging, sentiment analysis etc. Consumer reviews and comments are collected from various online platforms such as, The solution is being developed using R, SQL and data visualizations being displayed in Tableau.

Independently developing the end-to-end product.

Researching and validating advanced text analytics techniques/APIs such as Google NLP and LIWC- to validate which API works best with customer reviews collected from the web.

Integrating R and Tableau to present the results of the analysis in the form of an interactive dashboard with excellent slice and dice capabilities.

Completed data extraction, cleaning and transformation and exploratory data analysis within 3 weeks of starting the project.

Business Analytics Manager, CHI Franciscan Health (R, PowerBI, SQL, Excel) Oct 2017 – May 2018 Opportunity analysis project for increasing capacity utilization of the operating rooms across all CHI Franciscan hospitals. Extracted data using SQL and stored in SQL Server Management studio.

Analyzed about 500k records and developed a predictive model to predict the capacity utilization of operating rooms of CHI Franciscan hospitals after consolidating surgical specialties to specific locations.

Provided three recommendations for increasing the current operating room utilization by 30%.

Presented results to senior leadership on Power BI dashboards.

I was also the manager of my team of 3 people. Had multiple meetings with the client to gather business requirements, understand their pain points, translate data insights into business opportunities and give estimates.

Senior Software Developer/Data Analyst, Flextrade Inc Jan 2016 - May 2016 Implemented trading algorithms like Multi Leg spreads, MxN baskets, Volume Weighted Average Price while making sure the system has low latency and high throughput for Flextrade’s execution management system. Programmed using C++ and tested using google test library.

Wrote high quality code ensuring all requirements are met.

Delivered a project in 3 months with 100% certification testing.

Built metric dashboards to monitor KPIs for measuring health of the system. Advanced Software Developer/Analyst, Amdocs Jul 2013 - Jan 2016 Designed and developed robust billing solutions for tier I telecom and cable Industries using C++ and SQL. Owned complete software development life cycle from development to testing to deployment.

Participated in requirement gathering and updated the clients with the deadlines and ongoing issues.

Mentored new college hires in my team and imparted project knowledge to bring them up to speed. Software Developer, IBM Jul 2011 - Jul 2013

Development and maintenance GMIA Powerhouse Direct Delivery System using IBM powerhouse and Shell Scripting for managing aftersales business of General Motors.

Owned full development cycle of a module for generating invoices and deployed the project successfully without any missing requirements.

Successfully migrated legacy system from Solaris to Fedora with zero downtime.

Awarded IBM’s Eminence and Excellence Award for outstanding contribution to one of the most critical projects in our org.


Technical skills: C/ C++, R, Shiny, SQL, Python, Machine Learning, Neural Network, Hadoop, Advanced Excel, Perl Scripting, Shell Scripting, XML, Probability and Statistics, Decision Theory. Business Analytics Tools: Tableau, Power BI, Azure Machine Learning Studio, Google Cloud Platform. Projet Management Tools: MS Project, Smartsheet, Kanban, MS Excel Areas of Interest: Data Mining, Regression Modeling, A/B Testing, Social Media Analytics, Analytical Decision Making, Linear programming, Big Data Management and Strategy. Academic Projects

Heart Disease Prediction ( SVM, Neural Network, Decision Tree, Logistic Regression)

Developed a classification model for predicting whether a person may have a heart disease or not.

Developed an ensemble model of 4 different classification algorithms – SVM, Neural Network, Decision Tree

& Logistic Regression.

Achieved the model accuracy of 97.5%.

Optimal Warehouse Location (R, Linear Programming, Tableau, Power BI)

Identified the optimal warehouse from a list of potential warehouses which could cover maximum zip codes using 2-day shipping with minimum cost.

Developed regression model to analyze the relationship between distance from warehouse to customer, delivery duration and cost.

Used linear programing for identifying the optimal warehouse location based on distance between the warehouse and the zip codes in the seller’s distribution profile. Customer Churn Prediction (R, Decision Trees and Neural Networks, Azure Machine Learning Studio)

Developed a classification model for predicting whether a subscriber will churn from a telecom service provider using classification algorithms- Decision Trees & Neural Networks.

Validated the model using k-fold cross validation.

Predicted the customer churn with 92% accuracy.

Music Recommender System (Python, Sentiment Analysis, Data Mining Algorithms)

Developed a music recommender system in Python using hybrid recommendation technique.

It recommends songs based on content such as artist, genre, user behavior & similarity such as age, gender and demography.

Research Project

Analysis of annual financial reports to identify fraudulent companies using Text Mining

Performed exploratory data analysis on the financial document Form 10-K submitted by companies to SEC quarterly a year. Created word frequency plots, word clouds, N-grams and sentiment analysis to establish whether a company is committing financial fraud.

Applied text mining and machine learning algorithms such as clustering, classification, topic modeling and part of speech tagging to categorize the documents and understand the syntactical meaning of the text.

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