We provide IT Staff Augmentation Services!

Statistical Data Analyst Resume

2.00/5 (Submit Your Rating)

SUMMARY

  • Certified statistical business data analyst with more than 5 years of experience in statistical analyst, market studies, SAS developer, and SAS analysis
  • Certified data miner with experience with advanced predictive modeling skills using SAS EM, EG, JMP, and forecast studios
  • Certified base SAS programmer with extensive experience working on SAS/BASE, SAS/STAT, SAS/MACRO, SAS/GRAPH, SAS BI, SAS/ODS
  • Experience in dealing with big datasets, combining datasets, exploring data, model fitting up to scoring
  • Expertise in preparing statistical reports, generating summary reports, tables, histograms, graphs with analysis, and ad hoc requested reports
  • Extensive SAS programming experience with PROC SQL, UNIVARIATE, MEANS, GLM, ARIMA, Report, Tabulate, Transpose, Plot, Chart, and SAS/STAT Procedures
  • Experience delivering analytic report in different formats including CSV, HTML, RTF, PDF, and customizing reports using SAS ODS, PROC report, and SQL pass through facility.
  • Good knowledge of data extraction and sorting data from various databases: Teradata MS Access, SQL server
  • Extensive practical ability working on multiple regressions, logistic, multinomial regression, and neural network
  • Extensive experience with advance model fitting using principles component, PLS, LARS,LASSO, and more
  • Experience with high performance modeling using gradient boosting, random forest, credit scoring, and more
  • Experience with advance data mining using rule induction, incremental response, two stage modeling and more
  • Practical econometric modeling: ESM, AR,ARIMA, Credit scoring - survival and hazard analysis
  • Experience and training in quantitative and qualitative research data analysis and feasibility studies
  • Excellent organizational, interpersonal, and communication skills

PROFESSIONAL EXPERIENCE

Confidential

Statistical data Analyst

Responsibilities:

  • Appraised small business proposals, profitability, and market analysis
  • Accomplished several multiple regressions, logistic, multinomial regression, and neural network works
  • Managed statistical analytic system performance evaluation of different clients
  • Identified and recommended best practice methods, installed, implemented and gave remote supports.
  • Lead analytic team to select, design efficient and cost effective data acquisition, processing, analysis, and auto updating spread sheet formatting, linked quantitative table generation for prompt solutions
  • Analyzing American coffee import and export trade through each ports
  • Conducting demand analysis of different coffee types in harmonized codes for the coming years
  • Built predictive modeling of imported coffee by type, code, value and quantity for the coming five years

Environment: Base SAS v9.3, SAS/Macros, SAS/SQL, SAS Enterprise Guide, SAS Enterprise Miner, SAS/ACCESS, SAS/STAT, Teradata, Project Management, Basel II, UE Studio, Windows XP, UNIX

Confidential

Statistical data Analyst

Responsibilities:

  • Analyzed crime data of seven cities, seven data sets of daily records provided to be analyzed
  • Merged different big data sets using SAS,JMP, SAS EM, SAS EG
  • Conducted data transformation, Interpolation, imputation, splitting, fit the model, compare the model
  • Conducted advance Model fitting, Nominal logistic for categorical response analysis
  • Conducted advance Model fitting, neural network and Regression for rate response analysis
  • Built advanced predictive models, and time series model fitting based on the estimates, and scoring
  • Conducted advanced forecasting of ten years using SAS forecast server

RESEARCH ASSISTANT / GRADUATE ASSISTANT

Confidential

Responsibilities:

  • Organized research data, compiled, formatted, and merging different data sets
  • Analyzed the theoretical and economic interdependence of data trends
  • Diagnosed the distributions of raw data, statistical exploration, standardizing and transformations
  • Identified functional relationship of variables and derivation of economic variables
  • Analyzed statistical exploration of candidate variables and variable selection
  • Examined distribution analysis, outlier detection, hetroskedasticty tests
  • Built Econometric models, evaluated estimated model results, conceptual, and functional validation
  • Conducted risk analysis based on econometric model outputs

Environment: Excel solvers, Excel risk analysis platform, Maple, R, Gretel, STATA, Base SAS v9.2, SAS/Macros, SAS/SQL, SAS Enterprise Guide, SAS/ACCESS, SAS/STAT, Oracle 10g, Teradata, Project Management, Basel II, UE Studio, remote server, Windows XP, UNIX

We'd love your feedback!