Category

Description

• Attractive office location
• Flexible time management
• Truly multinational and dynamic organization
• Multicultural environment and cross-functional hub location

• Competitive salary
• Annual bonus
• Strong work/life balance, flexible working hours
• Life and Medical insurance scheme
• Career Advancement & Competency Development
• Rewards & Recognition

• Develop, modify and de-bug programming routines (such as SAS or R) along with SQL queries used to extract, clean, manage, and analyze large databases for health outcomes research under senior guidance. Data sources include medical and pharmacy claims data, hospital data, electronic medical record data, and prospective observational study data.
• Translate the study design into algorithms to extract, analyze and report secondary data for Non-Interventional Studies (NIS) or interactive data visualization tools under senior guidance.
• Gain competence with core Real World Evidence (RWE) tools such as R, R/shiny, SAS, Impala SQL, git or JIRA.
• Contribute to RWE dashboard, NIS and predictive analytics projects as required.
• Gain competence with core machine learning and data mining techniques such as random forest, GBM, logistic regression, SVM, deep learning.
• Basic knowledge in dimensional reduction and R packages such as ggplot, plotly or t-sne.
• Maintain consistency and comply with company standards of the project documentation for observational studies and interactive data visualization tools, including programming, specifications of analysis datasets, tables, figures and listings under senior guidance.
• Conduct quality review in compliance with company standards and processes upon various stages of the projects under senior guidance.
• Support and contribute to standardization techniques in order to increase efficiency in deliverables under senior guidance.
• Comply with project timelines together with the RWE Research Analyst and proactively alert the project manager or department leadership on any risks related to the deliverables and the timeline.
• Attend meetings with customer on a regular basis.

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