• Independently develop, modify and de－bug programming routines （such as SAS or R） along with complex SQL queries to extract, clean, manage, and analyze large databases for health outcomes research. Data sources include medical and pharmacy claims data, hospital data, electronic medical record data, and prospective observational study data.
• Independently translate the study design into algorithms to extract, analyze and report secondary data for Non－Interventional Studies （NIS） or interactive data visualization tools.
• Collaborate with the Research Analysts to scope and design projects under senior guidance.
• Use tools such as R, R/shiny, SAS, Impala, git or JIRA.
• Conduct observational data analyses including data management and statistical programming as well as the development of dashboards.
• Use machine learning and data mining techniques such as random forest, GBM, logistic regression, SVM, deep learning.
• Be familiar with dimensional reduction and R packages such as ggplot, plotly or t－sne.
• Independently 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.
• Independently conduct quality reviews in compliance with company standards and processes upon various stages of the projects.
• Independently support and contribute to standardization techniques in order to increase efficiency with deliverables.
• Comply with project timelines together with the Research Analysts and proactively alert the project manager or department leadership on any risks related to the deliverables and the timeline.
• Interact and engage with the customers on a regular basis by providing regular updates on the project progress under senior guidance.
• Present results, project summaries, and analytical techniques to customers, stakeholders and internal audience under senior guidance.
• Professionals with Bachelor’s degree or Master’s degree or PhD in computer science, bioinformatics, biostatistics, statistics or similar.
• Has at least 2－5 years of SAS or R professional programming experience for purposes of data manipulation, analysis and visualization.
• Has an interest in developing programming, statistical, visualization and analytical skills.
• Possesses exceptional problem－solving abilities with a good understanding of statistical methods （regression, Anova, t－tests, etc.）.
• Has good knowledge of SQL querying using at least one of the following Hive, Impala, MySQL, OracleSQL or similar.
• Has experience working as programmer or data scientist in the pharma industry, contract research organization, or academic institute; or experience in a closely related discipline.
• Has ability to prioritize tasks and communicate overall timelines in order to efficiently produce high quality deliverables.
• Possesses strong written/verbal communication skills.
• Highly effective at providing input at meetings, discussions and activities covering aspects of research data management and analysis on research projects.