Data State University

Sai Kaushik Oruganti

480-***-**** ********@***.***

https://www.linkedin.com/in/saikaushikoruganti 852 Marc Drive, North Brunswick, NJ, 08902 Summary:

Data analyst with background in statistics having 2 years of experience in data analytics, marketing analytics, data visualization, statistical modelling, predictive modelling, and forecasting. Passionate individual with high attention to detail having strong analytical and communication skills seeking a full time opportunity. Education:

Master of Science in Industrial Engineering Dec ’16 Arizona State University, Tempe, AZ GPA - 3.89/4.0 Bachelor of Engineering in Automobile Engineering Jun ’14 Manipal University, Manipal, Karnataka, India CGPA- 8.43/10 Technical Skills:

Programming Languages: R, Python, SQL, AMPL, Visual Basics. Analytics Tools: Tableau, Weka, JMP, Minitab, Qlik View, Advanced MS Excel, Google Analytics. Quality Tools: Lean six sigma, FMEA, SPC, 5S, VSM, Root cause analysis, Gage R&R, KAIZEN, KANBAN, DFSS. Database: MySQL, MS Access.

Data Analysis: Lasso Regression, Ridge Regression, PCA, Logistic Regression, ANOVA, Random forest, Clustering, Ensemble methods, Neural Networks.

Professional Experience:

Process Improvement Intern at Mahindra and Mahindra, India. Jun ’13- Aug ’13

Analyzed the displacement of wheel arch from the engine mounting using regression analysis and lean six sigma tools.

Achieved 28% reduction in the defect and was well appreciated. Campus Safety Enforcer at Arizona State University, Tempe, AZ. Mar ’16 – Dec ‘16

Monitored pedestrian activities in the campus and recorded the trends.

Scheduled the adjustments and location allotment based on the trends. Data Science Intern at Replete Health, Inc., AR, USA. Feb’17 – Present.

Acquiring data from multiple sources and performing data integration and data cleaning.

Conducting meta-analysis using machine learning techniques to identify business opportunities.

Reporting insights from data using Tableau, Microsoft word and PowerPoint. Academic Projects:

Examining the compressive strength of concrete with R, Minitab and Tableau.

Studied the variation in compressive strength of concrete to identify key factors using regression analysis.

Processed data and the best equation is modeled using stepwise regression in R and Minitab eliminating the problem of multicollinearity and unusual variance (Box-cox transformation) along with increasing adj. R-sq. value. Built a Healthcare risk model to forecast the possibility of having a cardiovascular event using R and Python.

Processed data to deal with missing data, inappropriate observations and duplicate data records.

Designed a logistic regression model based on several variables such as smoking status, total cholesterol, Systolic blood pressure, High density lipoprotein etc. and reported the analysis using Tableau. Developed a decision support system with security and interface usability features for a car rental company.

Built an ER model in Visio, translated it into a relational model and implemented it using MySQL and MS Access.

Developed windows and web applications using Visual basics integrated with Access and extracted relevant data by writing SQL queries.

Developed a classification model to predict the outcome of a nominal output variable using Random Forest algorithm.

Built a predictive model on a data set having 51 variables using data mining techniques in WEKA.

Up-sampled the data to account for class imbalance and used random forest classifier to minimize the balanced error rate. Built at Predictive model on a dataset consisting of 254 variables using Python.

Processed the data using data imputation methods to substitute missing values and removed multicollinearity.

Divided the data into train and test datasets and analyzed using machine learning techniques such as linear regression, random forest, support vector machines to compare predictive accuracy. Design of Experiments to Analyze the Performance of Basketball and football players using R and JMP.

Designed an experiment which was performed to analyze their agility, speed, etc. on different paths.

Analyzed the data using R and JMP concluding that the football player was agile and quicker. Certifications:

The Data Scientist’s Toolbox by Johns Hopkins University on Coursera, 2016 – Present, License: 5HYNASFGML5

Tableau 9 for Data Science on Udemy, 2016 – Present, License: UC-9YZZ5O24

R Programming by Johns Hopkins University on Coursera, 2016 – Present, License: E3NQPWVJQ5U3 Achievements:

Received Academic commendation for excellent academic performance, Arizona State University, Fall ’15, Spring ’16

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