SUMMARY

• Advanced SAS certified professional with around 8 years of extensive experience in Marketing Data Analysis, Statistical Modelling, developing methodological designs and analyzing data by using statistical techniques and SAS software.
• Experienced, Certified SAS Programmer and Data Analyst with extensive experience in Advertising, Media, Retail industry, CPG, Banking & Finance, and Business Consulting
• Excellent analytical skills for understanding the business requirements, business rules, business process and detailed design of the application
• Experience in handling complex processes using SAS Enterprise Guide, SAS Enterprise Miner, SAS/ STAT, SAS/ ODS, SAS/SHARE,SAS/CONNECT, SAS/MACROS
• Proficient with numerical data analysis including descriptive statistic and inferential statistics, categorical data analysis, predictive modeling, statistical survey sampling and analysis, survival analysis
• Experience with converting research objectives into well - defined statistical hypotheses to develop investigation and study design
• Experience in processing large datasets with billions of records for data transformation including data cleansing, data profiling and applying business logic rules to incoming data
• Expertise in analyzing and coordinating trial data, generating reports, tables, listings, graphs using SAS procedures like PROC MEANS, PROC TABULATE, PROC REPORTS, PROC GPLOT, PROC SQL, PROC TRASPOSE, PROC GCHART, PROC APPEND etc.
• Excellent command in analyzing data and producing reports by using various SAS procedures, creating new SAS programs as well modifying existing SAS programs
• Expertise in creating datasets, tables, macros, views, stored procedures
• Experience in version control, creating documentation, a SAS program
• Highly developed knowledge of carrying out qualitative and quantitative research methodologies and data mining
• Strong track record of conducting advanced statistical analysis
• Data preparation for various statistical modelling, which includes data cleansing, descriptive statistics, missing data analysis, data validation and preliminary data reporting sample size determination
• Experience in SAS ETL phase to Extract, Transform and Load Data
• Well versed in presenting research findings and insights to both internal and external teams
• Possess a strong ability to adapt and learn new technologies and new business lines rapidly
• Excellent communication skills
• Good interpersonal skills, leadership qualities, capable of handling multiple tasks and priorities, self-motivated. High ability to understand and quickly apply new technologies and information

TECHNICAL SKILLS

Statistical: SAS Enterprise Guide, SAS Enterprise Miner, STAT Graphics, SPSS, R Studio

SAS: SAS/Base, SAS/SQL, SAS/Macro, SAS STAT, SAS/ODS, SAS/GRAPH, SAS/ACESS, SAS/Connect, SAS/Share

Database: Teradata, DB2, Netezza, Microsoft SQL Server, My SQL, Oracle, MS Access, Excel

Productivity: MS Office (Power Point, Outlook, Project, Excel, Access), VBA, Tableau

Operating Systems: Windows, UNIX

PROFESSIONAL EXPERIENCE

Confidential, New York

Marketing Analyst

Responsibilities:

• Import, clean, transform and analyze transactional and behavioral data to gather consumer insights
• Develop an Attrition Model using Logistic Regression
• Perform training, testing and validation of the model using various statistical techniques
• Use Decision Tree and linear regression techniques to prediction consumer behavior
• Analyze email and mobile app data to measure campaign response
• Perform segmentation analysis to define different groups of consumers
• Develop KPI matrix to measure customers’ relationship with the company
• Develop a predictive model to identify future customer engagement and churn
• Discuss requirements and present findings to the client
• Develop queries to extract raw data from Teradata
• Handle billions of records and extract business specific information
• Use PROC IMPORT to extract raw data from .TXT, .CSV files to SAS system
• Create large data sets using MERGE and SET statement and various table joins
• Conduct extensive data checks to ensure quality and reliability of the data
• Use various SAS procedures like PROC MEANS, PROC FREQ, PROC UNIVARIATE, PROC CORR to create Diagnostic plots and statistics for Exploratory Data Analysis
• Use DATA Step, PROC SQL, functions like PUT, INPUT, SCAN, TRIM, INDEX, SUBSTR etc. for data manipulation, variable transformation
• Used LOG(), SQRT() functions for variable transformations
• Use various SAS functions like: INTNX, CATS, LAG, MEAN etc to prepare customer level transaction data for analysis
• Examine data for duplicate records.
• Use Proc sort with NODUPKEY and NODUP options to eliminate duplicate records
• Develop fast, efficient and reusable Macro Programs
• Create macro variables in data step using CALL SYMPUT, CALL SYMPUTX options
• Use %NRSTR, %BQUOTE to mask special characters in macro variables
• Use data step function for macros, SYMGET, to hide login credentials
• Use PROC DATASETS with delete statement for efficient programming
• Use PROC SURVEYSELECT to generate random samples
• Used PROC REG to check Multi-Collinearity

Environment: Base SAS, SAS Enterprise Guide, SQL, SPSS, R, Teradata, Unix, MS Excel, MS WordSAS Marketing Optimization, Tableau, PowerPoint, Outlook

Confidential, New Jersey

SAS Statistical Data Analyst

Responsibilities:

• Worked with CEO, COO and Consulting Team to generate Benchmarking Reports for clients
• Developed program to map survey questions to table variables
• Used PROC IMPORT to import data from QUALITRICS generated .CSV files into SAS tables
• Implemented Array and DO Loop to clean, manipulate and rename data files
• Analyzed survey data and use it for reporting purpose
• Worked with Business Intelligence team to extract information required for strategic decisions
• Developed SAS programs to generate Benchmarking Index for companies
• Developed Macros, programs for data validation
• Used %Do, %IF %THEN for conditional programming
• Used PROC TEMPLET, PROC SGPLOT, PROC GRADAR, PROC SGRENDER to generate various graphics and charts
• Used PROC REPORT to generate heat maps for benchmarking purpose
• Used PROC COMPARE, PROC FREQ,PROC SUMMARY to validate programs
• Used DROP, KEEP, RENAME, COMPRESS=, OBS= options for efficient programming
• Used PROC APPEND to create tables for reporting purpose
• Used PROC MEAN, PROC TABULATE, PROC PRINCOMP, PROC UNIVARIATE, PROC CORR, PROC SUMMARY, PROC RANK, PROC TRANSPOSE and SAS Arrays for statistical analysis
• Used Output Delivery system (ODS) facility to direct SAS output to RTF, PDF and HTML files
• Used Microsoft Add-Inns for SAS to generate PowerPoint presentations for Clients
• Performed data analysis of Confidential ’s survey data
• Extensively used SAS Enterprise Guide, Microsoft Add-Ins for SAS, MS Excel for data cleaning, data importing
• Applied PRINCIPAL COMPONENT ANALYSIS to develop Auto Rank Program
• Developed Macros and programs to generate Diversity Score for companies

Environment: Base SAS, SAS Enterprise Guide, SAS Enterprise Miner, SAS STAT, SQL, Netezza, MS Excel, MS Word, SAS BI Server, PowerPoint, Outlook

Confidential, NY

Marketing Analyst/ Predictive Modelling Analyst

Responsibilities:

• Implemented data management plans designed to meet project deadlines
• Designed, implemented project-wide programs in SAS for data management and basic statistical analysis
• Developed attribution models, using data mining techniques like Logistic Regression, to optimize marketing campaigns increase revenue
• Used data mining techniques to build predictive models for entire life cycle of customer acquisition, retention and cross sell
• Provided segmentation for database marketing efforts, such as Decision Tree, CART, Cluster Analysis, and Customer Profiling
• Performed exploratory research and Identify segments and effectively use it for direct marketing campaigns
• Used Salesforce platform for effective Campaign Management
• Developed model to forecast impact of direct market campaigns for acquiring, developing and retaining customers
• Developed marketing matrix to manage dynamic customer interactions
• Tracked the model performance time-to-time and report the findings to senior management
• Conducted analysis on client consumer databases looking at profitability, transaction behavior, and demographic characteristics
• Performed Conjoin analysis, Experimental Design and perceptual mapping to help client for new product launch
• Developed SAS code to validate data of different portfolios
• Analyze website visit/ traffic data to understand source of visitors to the website
• Generated reports to track key business entities on Monthly, Weekly basis
• Designed and created parameterized SAS EG jobs for analyst and business users to execute for different scenarios using different parameters
• Generated SAS EG stored processes for client specific analysis
• Involved in documenting the process, all possible information about the application like SAS programs, Data files, source
• Responsible for statistical applications support and programming primarily in SAS, supporting Marketing team
• Involved in Import and Export of data files to and from SAS using PROC IMPORT and PROC EXPORT from Excel and various delimited text based data files such as .TXT (tab delimited) and .CSV (comma delimited) files into SAS datasets for analysis
• Used SAS/ACESS to access data from NETEZZA server
• Used SQL PASS THROUGH facility for NETEZZA to efficient data processing
• Performed quality checks to ensure reliability of the data
• Efficiently used PUT, INPUT functions and DATETIME formats for data manipulation
• Generated summary and performed data analysis using PROC SQL functions such as MIN(), MAX(), AVG (), SUM(), MEAN()
• Used PROC FORMAT to define FORMATS and INFORMATS
• Used ORDER BY, GROUP BY option for advanced data querying
• Created reusable SAS Macro to create tables, graphs for presentation to clients
• Efficiently used forward scanning macro rule
• Used macro functions like %INDEX, %SCAN, %QUPCASE, %SYSEVALF for data manipulation
• Developed reports in RTF, EXCEL, PDF, HTML format using SAS ODS facility
• Used procedures such as PROC FREQ, PROC REPORT, PROC TABULATE, PROC SUMMARY, and PROC TEMPLATE to create reports for clients
• Developed a standard procedures that enables users to flexibly define and score new portfolios

Environment: Base SAS, SAS Enterprise Guide, SAS Enterprise Miner, R Studio, Salesforce, Tableau, SQL, Netezza,MS Excel, MS Word, Tableau, PowerPoint, Outlook

Confidential, NY

SAS Statistical Analyst

Responsibilities:

• Applied predictive models for large database using SAS and internally developed data mining tools
• Used SQL Joins to get desired data from multiple tables
• Modified existing SAS programs and created new programs using SAS macro variables to improve ease and speed of modification
• Researched and applied algorithms for data mining
• Involved in building predictive models for Risk Analysis
• Worked with commercial mortgages team
• Analyzed the Customer Lifetime Value (CLV) to predict the value derived from the relationship with customers
• Participated in various statistical projects to build predictive models using traditional statistical models (linear and non-linear regression) and data mining type models involving large databases (big data)

Environment: Base SAS, SAS Enterprise Guide, SAS Enterprise Miner, SAS STAT, SQL, MS Excel, MS Word, Outlook

Confidential

Data Analyst

Responsibilities:

• Independently handled assignments as a Team Leader. Expertly acquired understanding of technical and functional specifications and delivered results as per client requirements
• Developedreportsasperbusinessrequirementsandcreatedvariousreports
• Performed data analysis, graphical presentation, statistical analysis, reporting
• Developed SQL code to execute in Teradata SQL Assistant to check transaction and account level data for audit purposes
• Involved in client interaction. Implemented their requirements into the program specifications with quality results
• Lead, guided and motivated teams in project execution & management

Environment: Pl SQL, Oracle, OBIEE, DB2, Teradata, MS Excel, MS Word, PowerPoint, SAS