Data Analyst

THULASIDASS POUNRAJ

Fremont CA ***** 510-***-**** **************@*****.***

LinkedIn: https://www.linkedin.com/in/thulasidass-pounraj-bb616466

SUMMARY:

●SAS Advanced Programming: Familiar with Version 9 Advanced SAS, Proficient in testing of analysis data and programming code to meet regulatory and company standards.

●R and R-Studio: Track record of using advanced statistical methods and experience in predicting using Machine Learning Algorithms. Performed A/B testing using R-Studio

●Python: Certified Data analysis and visualization.

●Tableau Advanced: Creating Parameters, filters, Group, sets, basic functions, blending and all visualization graphs.

●MS Excel: Created pivot tables. Designed and executed macros to automate data entry inputs. Formatted. Spreadsheets and workbooks for print, document reproduction and presentation.

●SQL: Strong ability to create and present reports using relational databases like SQL.

Experience:Overall 5 years of experience in data analyst field

Data Analyst at Randstad (Tesla). Hayward, CA Dec-2017-Current

Experience in parallel implementation and testing of the SAS and R models which are already built and rebuilt them if they are not functioning as expected.

Document the data reports and model results, and communicated with the team /manager to share issues and knowledge.

Involve in creating views, stored procedures, and custom SQL queries to import data from SQL server to Tableau.

Analyse requests generate data files using SAS and SQLPLUS

Perform back-end testing to verify the flow of data from the database to the front end

Using SAS Macros to produce drill down capability for the reports

Generate reports, tables, graph to identify market opportunities and recommended business strategies based on analysis of internal and external data sets.

Tableau Developer at Blue CUBE IT (Business Intelligence analyst). North Brunswick, NJ AUG -2017 -Dec-2017

Worked closely with the business users to gather requirements

Designed, developed, testing, and maintaining Tableau reports and dashboards based on user requirements.

Involved in trouble shooting of performance issues which was associated with Tableau reports.

Utilized Tableau server to publish and share the reports with the business users. Also involved in administration tasks such as providing access to the users and adding them to the specific group.

Trained the users and helped them to improve and maintain their reports.

Trained onsite team using and creating Tableau report.

Managed Testing cycle regarding the reports and dashboard utilizing onsite and in inshore resources.

Involved in Tableau server up gradation (version 10).

Statistical Analyst AT Tata consultancy SERVICES. (Nielsen P roject). Bangalore, India Jun-2011 – Dec- 2014

●Worked on Machine Learning Algorithms (Logistic regression, Naïve Bayes, k-NN, Decision Trees, Random Forests and Artificial Neural Networks) in Data Modelling and Data Evaluation.

●Generated report of assumptions in SAS environment using Normality, Breusch-Pagan and Linearity test.

●Extensively used PROC SQL and SAS/ODS for generating different output formats.

●Collaborated with data engineering team to expand data coverage.

Environment: SAS 9.4 in Windows, R-Studio, Microsoft EXCEL.

Accounts Payable, Cognizant Technologies Solutions. Sep-2008 –Jun -2009 Chennai, India

This Project is an Account Payable Project. Deals with the Out of Balance, Merging, E-processing. SUPERVALU is RetailBusinessownsmultipleproductsandtheymarketandselltheirProductsworldwide.

Education:

California State University East Bay (Jan 2015-May 2017)

Master’s in Statistics

PSG College of Arts Science, Coimbatore, India (Jun 2009-May 2011)

Master’s in Statistics

PSG College of Arts Science, Coimbatore, India (Jun 2005-May 2008)

Bachelors in Statistics

Coursework includes:

Statistical Theory, Advanced Statistical Inference(Minitab), ANOVA and Regression Analysis(SAS), Machine Learning and Data mining(R-Studio), SAS Programming, R Programming, Data Visualization(Tableau), Time Series Analysis Statistical Analysis(Python)

Technical Skills:

Languages: SAS, R, Python, d3.js, HTML

Tools: Minitab, Tableau, R-Studio

Databases: SQL, SQLite, MySQL

Packages: MS Office, Advanced Excel

Operating System: Windows, Linux

Projects:

Prediction and Classification Analysis on Airline Data:

Developed an average number of flight delays with machine learning algorithms (k-NN) and predicted the overall performance of late flights with and without flight numbers in models from “Airline on-time Performance Dataset” donated by Bureau of Transportation Statistics. Tests Performed: k Naïve Bayes Algorithm, Decision Tree, Random Forest (Classification) (R-Studio. SAS)

Time Series Analysis on Closing prices of Amazon Inc. Stock- (R-Studio, Tableau)

Performed Basic Time Series Analysis and autocorrelation function using ARIMA process on Amazon Inc. historical prices dataset extracted from Yahoo Finance Website. (R-Studio)

Regression Analysis of Wage & Multivariable- (SAS, Tableau)

Performed Multiple regression analysis on wage with 526 potential explanatory variables and validated the assumption of normality, equal variance, and independency in SAS.identified influential observations by using leverage value DFFITS, Cook’s distance. Applied Box-cox transformation and simplified model using backward selection and stepwise selection with evaluations of AIC, SBC, Adj R-sq. and Cp.

Prediction Analysis, Heart disease Analysis (Python, SAS)

Used SAS to create, read, update, and delete large data. Used SQL to cover exploratory data analysis, Summarized data and applied regression analysis though SAS to fit the regression model. Predicted by using regression equation whether the patient has the Heart disease or not.

STUDENT ACTIVITIES & LEADERSHIP (STATISTICS)

Member, CSU East Bay Data Science Club, CSU East Bay, Hayward, CA Different tutorials were taught each week; topics included: SQL, R, Map/Reduce procedures using Hadoop, H20 R Package/APL, Machine Learning algorithms: K-NN, Decision Trees, Random Forests, General Linear Models, Gradient Boosting Models, & Deep Learning. 1) Created a database with airline data from 1988, 2) Made predictions of people who perished on the Titanic, 3) Spectral Graph Theory project: utilized analytic methods for data visualization including spectral clustering and spectral embedding of graphs, 4) Data Science Pipeline project: retrieved, explored, and worked with Banking and Social Networking Data to create and work through a Data Pipeline, 5) Bay Area Route Finder project: Created driving directions for the Bay Area using A* (a popular A.I. algorithm).

ACHIEVEMENTS & PROFESSIONAL AFFILIATIONS (CHESS)

Member, United States Chess Federation (USCF)

USCF Rating 1714.

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