SAS Consultant

Company: ERP Cloud Technologies LLC                                                                                        (Nov’17 – Till date) 
Designation: SAS Consultant                                                                                      
Project: Access Management Mining (Role & Application) – The objective of this study is to define rules for the users with respective to their division, unit and group. So that state street can control the license access to their internal and external applications.  
Responsibilities:

• Consider the latest one year data from different applications and users of State Street.
• Consider 30 applications and the users associated with it in Teradata. 
• Executed Explorative Data Analysis (EDA) to understand the behaviour of the data. 
• Identified few interesting insights from data.
• Applied association rule mining algorithm for identifying the rules.
• Now, started implementing these rules unit to unit. 
• Transformed these rules and then moved to bigdata environment.

Environment: SAS 9.4, SAS Enterprise Guide, MS-OFFICE and Windows 2010. Company: Sun Soft Technologies INC                                                                                              (Mar’16 – Nov’17)
Designation: Sr. SAS Analyst                                                                            
Project: Employer Recommendation Engine – The objective of the recommendation engine is to identify the highly recommending insurance products for the employers based on their selection. This includes the attributes like age of the company, # employees (part time + full time), employee’s salary bucket, employee age bucket, industry of the employer and state of the employer….etc. Frontend of this application was developed in R Shinny which connects to SAS for extracting the relevant insurance products based on the decision tree model. 
Responsibilities:

• Participate in business functional requirement meetings with client and end users.
• Determines operational objectives by studying business functions, gathering information, evaluating output requirements and formats.
• Extracted the data from Teradata to SAS.
• Design new SAS programs by analyzing requirements, constructing workflow charts and diagrams, studying system capabilities and writing specifications. 
• Gathering the survey data from different sources to SAS environment.
• Tested the functionality related SAS architecture.
• Executed Explorative Data Analysis (EDA) to understand the behaviour of the data by using PROC FREQ, PROC UNIVARIATE and PROC MEAN’s.
• Providing final cleaned data back to Bigdata environment.
• Responsible to allocate Adhoc projects to the team by following agile methodology.

Environment: SAS 9.4, UNIX, MS-OFFICE and Windows 2010. Company: Infosys                                                                                                                                    (Aug’12 – Feb’16)
Designation: Sr. Data Analyst                                                                                  
Project#1: Target Price Forecasting – The objective is to forecasting the price of the Manufacturing Part Number (MPN) for the next 4 quarters based on the historical data. There are more than 1.6M unique MPN’s. So we divide the data into 2 parts based on their price (with change and without change in price) over quarter to quarter. Then implemented separated forecasting techniques for these two categories of data.                                                                                      
Responsibilities:

• Extracting the data from SAP HANA to SAS environment.
• Created new columns based on the existing columns.
• Divided the data into train and test samples.
• Executed Explorative Data Analysis (EDA) to understand the behaviour of the data. 
• Performed missing value treatment for the previous/later quarters missing data.
• Developed SAS codes with SAS STAT procedures for different forecasting methods like ETS, AUTO ARIMA, STL, MEANF, NAÏVE, SNAIVE and RWF.
• Created automated SAS codes for each of the forecasting method.

Environment: SAS 9.4, SAS DI, Teradata, MS-OFFICE and Windows 2010.                                                                
Project#2: X – Border Propensity Models – The objective of this model is to identify whether a customer will participate or not given an opportunity to participate in X – border travel on a given time. Build the individual models with respective to their type transactions like Face-to-Face (F2F), Electronic (ECI) and CASH. This model help the business to target right customers based on their transaction type.
Responsibilities:

• Extracting the relevant data from SQL server to the SAS environment.
• Created a final dataset from customer dimension and transaction tables.
• Developed macro programs to clean, validate and update data to perform data analysis.
• Modified existing datasets using set, merge, sort, formats, functions and conditional statements.
• Created multiple new variables from the existing data based on their transactional data.
• Divided the data into train and test samples.
• Implemented logistic regression algorithm and measured the model accuracy.
• Validated model accuracy with test dataset and scored the new customers.
• Automated these models and delivered to the business with complete documentation.  
• Coding SAS programs with the use of Base SAS and SAS/Macros for Adhoc jobs requested by Users.

Environment: SAS Enterprise Guide, SAS DI, MS-OFFICE and Windows 2007.
Project#3: Travel Segmentation – The objective of this study is to group the customer based on their travel attributes. Business wants to know key conditions out of data for segmentation. So that management can use these conditions for their future strategies.
Responsibilities:

• Extracting the relevant data from SQL server to the SAS environment.
• Created a final dataset from customer dimension and transaction tables.
• Developed macro programs to clean, validate and update data to perform data analysis.
• Modified existing datasets using set, merge, sort, formats, functions and conditional statements.
• Divided the time window into observation and performance window.
• Created multiple new variables from the existing data based on their transactional data.
• Divided the data into train and test samples.
• Implemented code to identify the solution.  
• Automated the process with the help of SAS MACROS and SAS EG.

Environment: SAS Enterprise Guide, MS-OFFICE and Windows 2007.
Project#4: Monthly Dashboard – Developed a dashboard that will help the business to see the usage of the cards (Credit & Debit) on monthly basis w.r.to their card categories like Signature, Platinum, Gold and Silver…etc. This dashboard also provides the activation status of newly issued cards. With this dashboard business can easily track the history over latest one year.