Statistical/Clinical Trials SAS Programmer, 4yrs exp., MS (Enola, PA)

Technical Summary:

Through knowledge in Base SAS and Advanced SAS programming including Correlation Analysis,Regression Analysis,Factor Analysis,Cluster Analysis,K-means, Conjoint Analysis, CART & CHAID Analysis,ARIMA forecasting. FICO and VANTAGE SCORE, Basel II agreement,Credit Score cards Developing. Linear Regression Models, Neural networks, Decision Trees,K.S test, Gini C-value. Advanced Data manipulation and Mining techniques, Scoring &Statistical Modeling, Data Modeling,Database Queries and Statistical Analysis.

Clinical Trials Phases I – IV in Pharmaceutical Industry, Code of Federal Regulations (21 CFR Part 11), Integrated Summaries of Efficacy (ISE) and Safety (ISS), Investigational New Drug (IND), New Drug Application (NDA), FDA , E3, E6, E9, ICH and other regulatory guidelines like CDISC models such as SDTM, ADaM, ODM and XML.

Expertise in SAS/BASE, SAS/MACROS, SAS/SQL SAS/STAT,SAS/GRAPH, SAS/CONNECT, SAS/ACCESS, SAS/ ETL, SAS/Enterprise Miner

• Good Knowledge in Statistical Modeling and Data Analysis with Degree in Mathematics and Statistics, knowledge in Micro, Macro and Financial Economics.
• Regression Modeling and Risk Management in Finance Sector.
• Risk analysis in Mortage,Insurance, finance/Banking sectors.
• Knowledge on Sample, Explore, Modify, Model and Assess (SEMMA) with SAS/Enterprise Miner.
• Data Extraction, Transformation and Loading using SAS/ETL
• Performing Data Step manipulations on various data sets of any volume using efficient and advanced SAS programming methods.
• Oracle Database extraction using pass through Sql facility using SAS/Access.
• Good Knowledge in Predictive Modeling, analysis of Linear models.logit models probit models and also using the procedures like,PROC FACTOR, PROC REG, PROC LOGISTIC,PROC GENMOD,PROC CATMOD, PROC GLM. Etc.
• Ploting Graphs using PROC GPLOT,PROC GCHART
• Proficient in the customization of business reports per the client requirements to include various SAS procedures such as PROC PRINT, PROC SUMMARY, PROC SORT, PROC REPORT, PROC TABULATE, PROC FREQ, PROC MEANS, PROC UNIVARIATE, PROC CORR, PROC GLM, PROC REG, PROC ANAOVA, PROC CLUSTER, PROC PRINCOMP, PROC TRANSPOSE, PROC CPORT, PROC CIMPORT, PROC SQL, PROC RANK, PROC ACCESS and Data _NULL_, ODS HTML.
• Dealt with descriptive and Inferential statistics using Proc Means, Freq, and Univariate Proc Glm, Proc T test, ANOVA, Proc npar1way, Proc Logistic, etc,.
• SAS Macro facility(Macro Variables,Macro functions,Macro options)
• MedDRA coding (System Organ Class, Preferred Term, lowest level Term) for adverse events and Who Drug coding for concomitant medication
• Knowledge in Safety datasets including Demographic data, Med. history, Adverse Events, Vital signs, Laboratory data, ECG and other study specific datasets.
• Knowledge in Efficacy datasets using various SAS/STAT procedures
• Well acquainted with Software Development Life Cycle (SDLC) processes.
• Knowledge in PK/PD modeling of Drug Development using WinNonlin
• Understanding Code of Federal Regulations (21 CFR Part 11), Integrated Summaries of Efficacy (ISE) and Safety (ISS), Investigational New Drug (IND), New Drug Application (NDA), FDA , E3, E6, E9, ICH and other regulatory guidelines like CDISC models such as SDTM, ADaM, ODM and XML.
• Thorough Knowledge and experience of Microsoft Office tools like MS Access, MS word, MS PowerPoint, MS Excel. Also possess good working knowledge in Internet based access and database usage.
• Excellent communication, analytical, interpersonal, presentation and problem solving skills.

• Statistical software : SAS 8/9, SAS/BASE, SAS/MACROS, SAS/SQL SAS/STAT, SAS/ACCESS SAS/GRAPH,SAS/CONNECT, SAS/INSIGHT, SAS/JMP SAS/ETL,SAS/ETS, SAS/Enterprise Miner, SPSS
• Microsoft Tools : MS Office (MS-Excel, MS-Word, MS-PowerPoint, MS- Access)
• Languages : PL/ SQL, SQL, C, JCL
• RDBMS : Oracle 8i, Tera data, MS SQL Server and DB2
• Programming : Mat lab
• GUI/Tools : Visual Basic
• Operating system : UNIX, MS WINDOWS XP/2000/NT/98, MVS

M.S. Mathematical Modeling and Simulation, BTH, Sweden 2005
M.S Mathematics, Andhra University, India 2002
B.S Statistics, Andhra University, India 1999
Scholarship Awarded: Erasmus Mundus scholarship.
Studies in Methods & Models in Quantitative Economics, Germany, 2006.

Work Experience:

TNT Export office Stockholm, Sweden. Dec 2005 - Sept 2006
Data Analyst

Responsibilities: Verifying invoices, Data entry, correcting the Error codes for any shipment, discussing with peers in data errors, updating the shipment details and about their tracking information in excel sheets etc., Responsible for sending the documents via Flight to respected destinies, Scanning the documents and keeping them in folders and other duties assigned by the Supervisor and Team Lead. Environment: UNIX & Windows

Birla Sunlife Insurance company Ltd, India. Aug 2003 - July 2004
Insurance Advisor

Responsibilities: Meeting the customers explaining about the company insurance policies and benefits which they get from the respective policy and help them to choose the best policy which suits them and giving the financial analysis of the policy.

Project: Comparison of Fuzzy sets and Rough Sets in Medical Diagnosis Model
Used Mathematical and Statistical concepts for creating the Medical Diagnosis Model and comparing the results to choose which patient should be given preference for diagnosis basing on their treatment diagnosis level.

Project on Queuing Theory: Model to predict Lengths and waiting times for customers needing Service M/M/1 Queue, M/M/m,/ M/D/1 calculating mean waiting times, mean time in the systems, mean Queue length, correlation how the factors are related. The simplest model in Queuing theory is M/M/1 it has single server. It assumes random arrivals, exponential service times. The customers are served first in –first out order. It is based on Poisson Arrivals and Service times. Calculating loss ratios mean interval times server utilizations and ploting the Graphs for the obtained results for the given arrival times and queuing specifications. Interpreting the results from the obtained Graphs and giving conclusions basing on the obtained results which server is best Assignments done with the concepts of Markov chains, Monte Carlo Simulation, Predictive Modeling Assignments with Operations Research , Linear Programming and Game Theory

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