Business Data Analyst Intern Resume

OBJECTIVE:

Graduate Student with 3+ years of work experience looking for full time position where I can develop high - performance, data-driven systems and advanced analytical models to translate business objectives into actionable analyses

SUMMARY

Strong analytical skills with expertise in cleaning and analyzing large data sets with Machine learning algorithms.
SAS Certified Statistical Business Analyst Using SAS 9.0: Categorical data analyses, ANOVA, regression and logit models
3+ years of experience in Data analysis and Application Development.
Hands on experience in creating predictive models, developing environment for data analysis.
Proficient in SAS, R, good knowledge of Python, SPSS
Comprehensive Knowledge on Visualization tools like Tableau, Qlik
Strong knowledge in Big Data Technologies-Hadoop, MapReduce, Search, Caching, CDN,Azure, Cloud,Spark, Kafka,Hive
Proficient in using RDBMS concepts, DDL, DML SQL queries with DB2 and MySql

PROFESSIONAL EXPERIENCE

Business Data Analyst Intern

Confidential

Responsibilities:

Spearheaded design and development of analytic software stack and workflows using SQL Server, R, SPSS, Python and Qlik
Develop predictive models to determine employee churn propensity and employability using Decision trees in R, SAS.
Used Python API for Watson analytics to get sentiments and tone of exit survey data
Implemented banking analytics use cases such as consumer insights, loan and credit card approval using, SPSS for a banking firm
Configured SAS environment on development platform (linux server), work involved configuring ODBC driver, running SAS batch code and writing, shell scripts, CRON jobs for scheduling the flow and automating the score output.
Created scripts to create tables, complex queries, views using SQL server
Writing SAS, R code and ETL transformations using SSIS for preparing the data model for predictive modelling.

Data Specialist

Confidential

Responsibilities:

Created ETL processes using SAS Data Integration Studio to load and transform data from various data sources.
Develop statistical sales forecasts through analysis of historical sales and seasonal patterns, weather, market intelligence, etc.
Prepared data/analysis upon clients's request, assisting in the preparation of reports for monthly meetings.
Managed end-to-end delivery of data flow from source systems to the reporting layer via the Enterprise Data Warehouse
Performed Root Cause Analysis on critical issues and applied fixes / changes within the specified SLA time frame.
Worked closely with client to provide reporting solutions using SAS Visual analytics and SQL Server
Extensively performed Data Cleansing during the ETL's Extraction and Loading Phase by analyzing the raw data and writing SAS code