Hiring for Biostatistician

Hiring for - Biostatistician DA TL & TM , SDMLocation - Pan IndiaHybrid ModeUS Night shiftsData Analyst : 3+yrs of exp in Biostatistician , ctc upto 16lpaTeam lead : Minimum 5+yrs of exp in Biostatistician , ctc upto 22lpaTeam Manager : 6+yrs of exp in Biostatistician , ctc upto 30lpaSDM : 10yrs of exp in Biostatistician , ctc upto 40lpaRequires 5+ years of relevant research/clinical/healthcare experience (2 less years required with PhD)Masters degree in Statistics / Biostatistics or Applied StatisticsPh.D. preferredSkills : #Biostistician, #MockShell, #Statisticalanalysis, #Modellingtable, #Biostatistician,#Linearregression. #Logisticregression, #Ttest knowledge, #Anova knowledge, #Ancova knowledgeKey ResponsibilitiesPreparation & Review of Sap & Mock shellEvaluates research concepts to develop appropriate statistical methods of analysisReviews protocols, writes statistical sections and Statistical Analysis Plans (SAPs) for assigned studiesDetermines methods of statistical analysis and applies statistical techniques to determine measures of central tendency, correlation, sample size, significance of difference, etc.Reviews CRFs and ensures complete data collection for analysisRuns randomization listsPrepares tables, charts, and graphs showing the results of statistical analysisPerforms specialized statistical analysis involving correlation equations for multi-factorial variances and regression equations.Discusses study conduct and results with physicians and sponsorsDetailed knowledge of SAS programming and procedures and other statistical software; writes edit checks in SAS; validates SAS programsResponsible for data transferAbility to provide technical solutions to a wide range of difficult problemsWorks with research staff to resolve issues regarding data capture, accuracy, and completenessAssists in the development of new statistical tools and modeling protocolsDocuments methods, instructions and rules for implementing new techniques and research toolsDevelops standard data quality review checks and validation proceduresDesigns predictive modeling programming for evaluating health outcomes, utilization, and costsProduces standard error analysis routines and protocols (missing data & data errors checks)Diversifies research techniques, by producing mixed qualitative-quantitative approaches to evaluating EHRs.Advanced SAS programming skills for data manipulation (macros, proc SQL, data and proc steps, merging, use of first & last from proc sort, removal of duplicates, running totals, merging, use of arrays, proc templateInterested candidates contact HR Umme @8655884775 / umme@careerguideline.net PRB