OBJECTIVE:

Seek a SAS programmer SQL developer position.

SUMMARY:

• Expertise on SQL, SAS base / STAT / Macros / EG / EM and validate data.
• Expertise on data visualization: SAS Enterprise Guide, Tableau
• Expertise on predictive modeling such as Cluster Analysis, Trend Analysis, Classification and Predictive Modeling, Logistic Analysis, Association Analysis using SAS Enterprise Miner (EM) and SAS Base. Expertise on statistical and machine learning techniques.
• Oracle RDBMS experience. SQL programming (using both SQL pass - through and PROC SQL via SAS/Access to Oracle databases, extract data from multiple table in Oracle dataset with merging, transforming and other data manipulations, and load table into Oracle through Oracle RDBMS.
• Extracted data from Web using beautifulsoup, Numpy and Confidential was used for data manipulation and data clean, Sklearn, Keras was used for machine learning

TECHNICAL SKILLS:

SAS Skills: SAS (server, BASE, STAT, MACROS, GRAPH, Enterprise Guide, Enterprise Miner ).

SQL Server: SSIS, SSRS, SSAS

Languages: PL/SQL, SQL, Toad, Python, R, Matlab

Databases: Oracle 11g, SQL Server 2012, MS Access, MA Excel.

PROFESSIONAL EXPERIENCES:

Confidential

SAS Programmer

Responsibilities:

• Visualization analysis and automate process.
• SQL and macro development
• Developed validation programs and dashboard grid file management
• Extract data from Web using beautifulsoup, then Numpy.
• Confidential, was used for data manipulation and data clean, Sklearn, Keras was used for data analysis.

Confidential

SAS Programmer

Responsibilities:

• Worked for large datasets, developed and evaluated SAS code and SAS macro system, Oracle database ETL and manipulations.
• Code optimization and SAS code Development
• Oracle database RDBMS connection and ETL
• Predicted bank phone service using predictive modeling
• Wrote CACS reporting dictionary / WI Instruction
• Database test case
• One SAS code need the process time was 7-9 hours, after I regenerated, it was reduced to 15 minutes by saves 95% time; another SAS program has above 6000 statements which process time was around 6 - 7 hours, was regenerated to process for 2 hours, saving 66% time.
• The two programs can offer daily report instead of monthly reports now.
• Extracted data from Oracle database using Toad, SAS pass through. Did extensively data manipulation within Oracle or SAS.
• Developed more than 20 reports, including MTG, AMX, Return Accrual, SBB, inventory and zt reports, which become standard monthly or biweekly report programs in Confidential, by reading flat text file and pass through Oracle database. Developed QC and QA method.
• Used time serial data forecast delinquency. Analyzed bank phone calls including in-call and out-call dataset to predict and re-organize phone service using time-serial forecast techniques.

Confidential

PL\SQL Developer

Responsibilities:

• Design sub-dataset pulling, data cleaning. Descriptive analysis. Data mining MVP (Most Valuable Population), PL/SQL developer.
• Sub-dataset were pulled from Oracle data warehouse using SQL or L/SQL from Toad.
• The goal is to standardize the database which is complicated dirty.
• I wrote PL/SQL function to extract the substring to get typical properties using Oracle analytic function, using lookup table and regular expression, such as Confidential Replace, Confidential Substr, among Confidential instr to standardize the street, email address and phone number.
• Exported to Excel or Microsoft Access.

Confidential

SQL developer

Responsibilities:

• Data Mining machine learning onbankinsuranceproduct to predict VIP people
• Data pulled from Oracle using SQL or Toad and modeled to predict insurance product usingmultipleLogistic regression andmultiplelinear regression within both SAS EM and SAS Base.
• Feature selection by using Proc Varclus and Proc Corr and Proc, then only 12 of 50 variables were selected, the interaction among continuous and categorical predictors will be included if necessary.
• After models validating, visualized results using ROC and LIFT.
• Multiple modeling results, such as Neural Network, Decision tree, Logistics, were compared.

Confidential

Research Data Analyst

Responsibilities:

• Created datasets and produced statistical reports and summary tables using SAS.
• Supported team works on SAS programming and statistical analysis.
• Developed programs for biomedical researching data and clinical data for integrated summary of safety analysis.
• Generation of efficacy and safety related TLF's (AE, PE, DM, VS, LB). QC and validating SAS code.
• Developed multiple report programs and created macros to de-duplicate rows, merge multiple tables using data step and SQL.
• Integrated statistical results obtained from GLM, MIXED, FREQ, ANOVA and MEANS procedures.

Confidential

Data Analyst

Responsibilities:

• Run multiple projects together and completed on time.
• Managed the data flow and integrate the data to a database.
• Contributes to cross-functional / cross-department / cross-institute raw data handling process.
• Analyzed research and medical data using SAS and SAS Enterprise Guide.
• Query against databases through the use of SAS SQL language.
• Conducted ad-hoc and post hoc on medical data and scientific data analysis and conduct accurate and appropriate interpretation of data.