Data Life Insurance

Ritika Sinha LinkedIn

** ********* ******, *** ******, US 267-***-**** ******.***@*****.*** ******.*****@*****.*** A highly motivated Data Science and Analytics professional with 3years experience as Data Scientist, Business Analyst and QA. Committed to and exploration, visualization, development and evaluation of business models to deliver top notch product result that can fuel growth in profit and revenue for fortune 500 clients. Expertise in Statistics and Predictive Modelling

EDUCATION

University of Connecticut School of Business, Master of Science in Business Analytics and Project Management 2016-2017 VIT University, Bachelor of Technology in Biotechnology 2008-2012 ANALYTICAL SKILLS

Statistical Skills: Predictive Modeling, Linear Regression, Logistic Regression, ANOVA, Correlation Analysis, Principal Component Analysis Cluster Analysis, Decision Trees, Data Mining, Data Visualization, Time series analysis, Neural Network, Hypothesis Testing, Text mining, Natural Language Processing, Recommender System, Dimensionality Reduction, Deep Learning, Random Forest, Data scrape from Word Document, PDF and XML files, Ensemble Models, Extreme Gradient Boosting

Programming Tools: SAS JMP, base SAS, SAS studio, SAS Enterprise Guide, Python, SAS Miner, Tableau, MS Visio, R, Rapid Miner, MS Excel using Analytical Solver, Excel Macros, Oracle SQL, MySQL, MS Project, HP Quality Center, QTP PROFESSIONAL EXPERIENCE

PFIZER INC, New Jersey, USA Finance & PGS BT, Data Scientist Intern Jun 2017 – Aug 2017

• Part of the Pfizer Global Supply Chain and Manufacturing Business Intelligence team and was responsible for delivering business value by helping with cost models, forecasting and solving product quality manufacturing and supply issues.

• Responsible for scraping data (data extraction) from different file formats like WORD Documents, PDFs and XMLs to CSV file by automating the process using Python and R. Developed R shiny Application for business to upload multiple XML reports and extract the data value from XML to CSV file. Created Visualization of Year over Year view of trends of drugs supply issues on the basis of drug product names and locations and also created word cloud for root cause analysis.

• Used python to develop predictive models to determine whether the drug will have any manufacturing defects or not in future.

• Built interactive data visualization using Tableau to provide business with actionable insights on manufacturing, packaging and supply issues for different drugs. Created statistical models using SAS base to predict the future supply issues for manufactured drugs in different Pfizer manufacturing locations. COGNIZANT TECHNOLOGY SOLUTION, Bangalore, India Business Analyst and QA May 2012– Nov 2014

• Involved in business requirement gathering, requirement analysis and interacting with cross-functional teams to ensure mutual understanding of process and application. Acted as a liaison between the client and the development team during the full SDLC phase of application development. Having wide exposure to various SDLC methodologies including AGILE and Waterfall.

• Responsible for testing Client CRM Application and Online Telecom Application in an Agile project environment. Maintained Requirement Traceability Matrix of the projects to ensure all technical and functional requirements are met and thus increased the customer satisfaction rate.

• Experienced in the STLC phases of Software testing. Executed Functional, Database and Regression test cases and automating these scripts through automation tools such as Selenium IDE for Firefox and Quick Test Professional. Involved in daily defect triage calls/discussions with Onsite Counterparts and Subject Matter Experts. Also worked on SQL reporting as per the client requirement.

• Worked as Offshore Test Lead for Vonage US Telecommunication client, and was part of telecommunication testing projects for US clients like MTS Allstream and Cox Telecommunication.

ACADEMIC PROJECTS

• LIMRA- Life Insurance Buyer study: Developed Stepwise LASSO Regression model to identify which demographic and behavioral factors greatly impacted on the decision of whether to apply for life insurance quotes (Quote vs No Quote) and also to identify which factors impact the decision to purchase or not purchase Life Insurance

• Bank Revenue: Forecast the profitability of the Bank in terms of revenue: Developed Stepwise regression model to predict the revenue contributed by the bank customer, using the dataset from the Kaggle.com. Tableau tool used for visualization of data to study the trends and patterns between the variables and base SAS was used to build the model. Evaluated the stepwise model based on Mallow’s Cp, Bayesian and Akaike criteria. Model explained 60% variability.

• Sales and Inventory Management Data Analytics using R: Developed Ensemble, Decision tree and Random Forest model to predict items to be retained in the inventory. Created an interactive web application using R shiny to which allowed user to plug different basic attribute values and find out the status of various item in the inventory.

• Time Series Forecasting of Weekly Walmart Sales Data: Built recommendation for future prediction of Walmart sales using ARIMA and Exponential Smoothing algorithm forecasting with an accuracy of 76% using mean absolute percentage error metric.

• Forecast Taxi Booking Cancellation: Developed a logistic model from the past Taxi cancelled dataset to reduce the future taxi Cancellation and increase the profit. Explored the supervised learning techniques: Logistic Regression, Decision Tree, Neural Network in SAS JMP. Evaluated the best model on the basis of Accuracy (78.89%), Misclassification rate, Lift Ratio and Cost Benefit Analysis.

• Prediction of Restaurant Revenue: Developed a mathematical model using Wrapper algorithm to increase the effectiveness of investment in new restaurant sites. Data preprocessed to remove outliers and data transformed to normalize the dependent and predictor variables. Evaluated the best model using Bootstrap forest based on the RMSE value.

• Burger House: Process Modelling: Developed an improved business process model, ER model and Oracle database for the Burger House using MS Visio and Oracle SQL. New process improved management of customer records, daily and weekly deals and rewards points offered to customers. AWARDS CERTIFICATIONS AND EXTRACURRICULAR

• Certified ISTQB – Foundation level Tester. Level 0 and Level 1 certification in Telecommunication. • Published paper in the Research Journal of Pharmaceutical, Biological and Chemical Sciences. • Appointed as Career Ambassador for UCONN MSBAPM • Summer Internship in BioAxis DNA Research Center, India

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