Hiring for Biostatistician - Hyderabad, India - Career Guideline

Description

Hiring for - Biostatistician DA TL & TM , SDM

Location - Pan India

Hybrid Mode

US Night shifts

Data Analyst : 3+yrs of exp in Biostatistician , ctc upto 16lpa

Team lead : Minimum 5+yrs of exp in Biostatistician , ctc upto 22lpa

Team Manager : 6+yrs of exp in Biostatistician , ctc upto 30lpa

SDM : 10yrs of exp in Biostatistician , ctc upto 40lpa

Requires 5+ years of relevant research/clinical/healthcare experience (2 less years required with PhD)

Masters degree in Statistics / Biostatistics or Applied Statistics

Ph.D. preferred

Skills : #Biostistician, #MockShell, #Statisticalanalysis, #Modellingtable, #Biostatistician,#Linearregression. #Logisticregression, #Ttest knowledge, #Anova knowledge,

#Ancova knowledge

Key Responsibilities

Preparation & Review of Sap & Mock shell

Evaluates research concepts to develop appropriate statistical methods of analysis

Reviews protocols, writes statistical sections and Statistical Analysis Plans (SAPs) for assigned studies

Determines 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 analysis

Runs randomization lists

Prepares tables, charts, and graphs showing the results of statistical analysis

Performs specialized statistical analysis involving correlation equations for multi-factorial variances and regression equations.

Discusses study conduct and results with physicians and sponsors

Detailed knowledge of SAS programming and procedures and other statistical software; writes edit checks in SAS; validates SAS programs

Responsible for data transfer

Ability to provide technical solutions to a wide range of difficult problems

Works with research staff to resolve issues regarding data capture, accuracy, and completeness

Assists in the development of new statistical tools and modeling protocols

Documents methods, instructions and rules for implementing new techniques and research tools

Develops standard data quality review checks and validation procedures

Designs predictive modeling programming for evaluating health outcomes, utilization, and costs

Produces 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 template

Interested candidates contact HR Umme @ /