The ideal candidate will be familiar with uploading raw data into the SAS as well as performing ETL and data cleansing in Base SAS or Enterprise Guide. The candidate will also be required to be knowledgeable in basic statistical procedures within SAS to summarise data and produce basic descriptive statistics.
The candidate must have hands on experience in writing SAS programs, preferably including SQL and macros, whilst having the opportunity to project manage the work to ensure that it meets the time, cost and quality whilst maintaining excellent documentation throughout the process.
The candidate must also have experience in gauging the timescales for any tasks that are carried out and to take full ownership of the delivery of the work. The candidate must be able to communicate the progress and produce status reports to key stakeholders to ensure that tasks are being progressed in a timely manner and that all issues are raised, managed and resolved.
The candidate will be at least graduate level and will use their business acumen to elicit business requirements and convert these into technical or analytical solutions to obtain the answers required.
A good knowledge of Base SAS (preferably including SQL and macros) and SAS/STAT or Enterprise Guide and writing queries to interrogate data is essential. Knowledge of MS Excel is essential especially to be able to extract data into user friendly pivot tables so that users can interrogate data.
Job Purpose
To drive the formulation and/or optimization of customer management and risk management strategies using a variety of data driven analytical techniques including but not limited to customer profiling, segmentation and predictive modeling. A key aspect of this role also covers a significant data management and MI reporting element which includes data extraction for campaign execution, data preparation for analysis, production of monthly and weekly data sets and MI reports as well as performing data validations such as the creation of data quality/integrity reports and documentation of data dictionaries.


- N/A

- Maidstone