Data Analyst Intern Resume Houston, TX - Hire IT People

SUMMARY:

looking for a position in Data Science domain with hands - on approach to tackling projects and accomplishing goals.
Passionate about gleaning insightful information from data assets and developing a culture of sound, data-driven decision making.
Experienced with machine learning algorithm such as logistic regression, KNN, SVM, random forest, neural network, linear regression, lasso regression and k-means

TECHNICAL SKILLS:

Programming language: HTML, CSS, C, C++, R, Python (NumPy, SciPy, Pandas), SAS, Java, Ajax, Perl, MATLAB, Scala

Business Intelligence tools: Tableau, OBIEE, Splunk, SAP Business Objects, QlikView

Development Tools: Microsoft SQL studio, IntelliJ, Eclipse

Databases: NO SQL, PostgreSQL, MySQL, Microsoft SQL Server 2008

Reporting Tools: MS Office (Word/Excel/Power Point/Outlook), SSRS

EXPERIENCE:

Confidential, Houston, TX

Data Analyst Intern

Responsibilities:

Data Analysis-Data collection, data transformation and data loading the data using different ETL systems like SSIS and Informatica.
Performed source to target mapping as part of data migration from JD Edwards system to Agile PDM system.
Data Migration testing and implementation activities using SSIS and SSRS tools of Microsoft SQL Server 2008.
Responsible for accuracy of the data collected and stored in the corporate support system.
Performed data review, evaluate, design, implement and maintain company database.

Confidential

Associate Software Engineer

Responsibilities:

Documented the technical specification for the reports and tested the generated reports.
Gathered user requirements and created the business requirements documents, used the technical document to design tables.
Prepared test plans for various modules.
Created and managed Databases and optimized the SQL queries for improved performance.
Created Database triggers to maintain the audit data in the tables and prepared test plans for various modules
Developed worksheets using parameters Blend, Join, calculate data to analyze the data set and visualize data in form of various chartsplots and maps.
Designed different Dashboards to analyze the data related to customers, sales and services by applying actionable insights.
Loan prediction data set using R
Customer details gender, marital status, income, loan amount, credit history is studied and percentage of Loan approval is predicted.
Loan status is set as target value and compared by other variables like loan status by income, loan status, Credit history and a model is developed to predict the target variable.
Decision tree model is used to base the predictions on the variables and the result of loan status.