My career as a data analyst/statistician has encompassed a variety of environments (building society, insurance, pharma, academia) using various platforms. I have used SAS to input, verify, modify, aggregate, quality control and model data arising from many different sources including Excel, Access, relational databases, and paper. Excel has frequently been used for output from SAS programs. Statistical methods and procedures have been used to model and explore data (eg. assessing the importance of explanatory variables, trends, outliers, and data integrity for incompleteness and inconsistencies). Regression (logistic, mixed, failure-time) and graphical techniques have been used in this, also plots of high-dimensional data. Proc SQL queries have been developed for large datasets (eg. GPRD: 70 million rows). I have participated in large-scale data migrations and wrote a technical critique of methods and limitations in the transfer of data between machines of different architectures. Other work has included assessing data and methods in the automation of processes involving manual intervention. As per the normal regulatory-based approach required in the pharma industry, I am accustomed to documenting data requirements, definitions, and programs; also to writing programs in a well-commented, efficient and intelligible form.