Sales Data

Suyash Porwal

480-***-**** ********@***.*** linkedin.com/in/suyash-porwal 1216 E Vista Del Cerro Dr, #1109, Tempe, AZ 85281 SUMMARY OF QUALIFICATIONS

Graduate student with 3 years of experience in Data Analytics, Database Development, Data Visualization, Computational Statistics and Business Intelligence with advanced skills in Python, R, SQL, Excel, MATLAB, SAS, Tableau, CRM and Report Generation PROFESSIONAL EXPERIENCE

Data Analyst, Navratna Creations Feb’15 – Aug’16

Designed relational database to monitor customer demand and performed complex queries to extract insights using SQL

Generated complex stored procedures, triggers, tables, views using SQL Server improving database performance

Created visually impactful dashboards in Excel and Tableau by Pivot tables and VLOOKUP growing 11% data reporting efficiency

Forecasted sales of 24 designs by Time Series Analysis considering seasonal effects, reducing inventory cost by 13 %

Performed Regression analysis to study customer behavior and their purchasing habit to offer them a better pricing using R Project Engineer, Pinnacle Industries Ltd. Jul’13 – Jan’15

Developed key performance indicators and scorecards to monitor product sales and operations of vendors using MYSQL

Predicted demand of 38 products sold to 3 million customers worldwide using Python to reduce spare parts inventory by 19%

Built visualization for Sales data and department spend analysis for more than 30 products using Tableau to optimize revenue

Extracted procurement data of different vendors using SQL and performed statistical analysis to predict scheduled delivery

Prepared quarterly reports on expenditure of Automotive interior parts using Power BI RELEVANT PROJECTS

Building the classification model to determine balanced error rate on a dataset having unbalanced classes Fall’17

Preprocessed the training instances to balance classes using a combination of resampling and minority oversampling technique

Determined classification model that minimized error rate using ensembled techniques like bagging and boosting in Weka Computational Statistics- In depth study and application of Statistical Models Fall’17

Built and analyzed predictive models by least squares, least absolute deviation, logistic regression and nearest neighbor methods

Performed feature selection on high dimensional data by penalized estimation ways like ridge regression lasso and adaptive lasso

Conducted a Monte Carlo study to investigate coverage probabilities of bootstrap confidence intervals for the selected attributes Forecasting of sales of Recaro car seats Spring’17

Predicted revenue by linear regression and analyzed current market position by achieving model R-square (adj) value of 0.92

Reckoned factors that affect the sales by applying Stepwise Regression and Principal Component Analysis using R, MATLAB Design of Database Management System and User Interface for effective functioning of Textile Industry Spring’17

Built a relational model using Entity-Relationship modeling between all personals related with the company with MySQL and VBA

Executed SQL queries to analyze demand and supply and evaluated ideal inventory by generating reports using XML and DTD Alerting and diagnostics from historical data for Heart Disease patients using R Fall’16

Identified risk factors that are associated with increased heart disease and built logistic regression model to predict heart disease

Validated the model by ensuring that it performs out of sample and on different populations other than training set population Predicting housing prices in Boston area using observational Data using R Fall’16

Predicted house prices using all the variables and built regression trees to predict the median price at each leaf of the tree

Evaluated the most important factors impacting the prices by applying cross-validation to regression tree and generalized results EDUCATION

Master of Science in Industrial Engineering: Specialization in Statistics and Data Sciences Est.May’18 Arizona State University, Tempe, G.P.A. 3.37/4.0

Bachelor of Technology in Production & Industrial Engineering Jul’09 – Apr’13 Maulana Azad National Institute of Technology, India, G.P.A 3.50/4.0 TECHNICAL SKILLS

Programming Languages: R (2 yr Python (Numpy, Pandas, Matplotlib, Sklearn, Seaborn) (2 yr MATLAB (1 yr.+)

Statistical software: SQL (3 yr Tableau (1 yr. +), SAS (1 yr SPSS (2 yr SAP, JMP, Weka, Minitab, VBA(Macros), Power BI

Database Management System: MYSQL (3 yr PostgreSQL (1 yr SQL Server (1 yr Microsoft Access, Microsoft Azure

Machine Learning Concepts: SVM, ANN, PCA, KNN, Boosting, Bagging, Bootstrapping, Clustering, Regression, Decision Trees

Related Courses: Machine Learning, Time Series Analysis, Computational Statistics, Data Sciences, Distributed Database System

Certifications: Advanced SQL for Data Scientists, Python Data Structures, Essential Statistics for Data Analysis- Excel, R Tidy-verse

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