In an increasingly networked world, driven by the need for greater efficiencies and a more sustainable planet, the use of data to make intelligent decisions has become a global priority.
The objective is to build a propensity model that provides UK business users with dynamic, relevant insight into their target markets and allows them to make informed decisions on a potential client’s propensity to buy
The project will further the understanding of how buyers and sellers will behave in markets that become more transparent and where needs can be more easily identified.
This will be achieved by building models to harvest specific information from unstructured sources that are then mapped into a semantic repository of companies that incorporate the entire UK economy. The model will enable extraction and presentation of information with the aim of identifying the semantic relations and queries that will determine an organisations ‘propensity to buy’ given a ‘sales proposition’. Innovations also investigated will look at semantic annotation of the provenance of the content, allowing the combining of information artefacts from different sources and creating algorithms that measure degrees of confidence for any data point.
An ideal candidate will have a strong background in time series analysis, and statistics. Experience of Semantic Web, specifically OWL and RIF and python or JAVA is essential.
Other experiences that are not essential but highly useful are; marketing, economics, NLP, SOLR, Nutch, and GATE.
Some knowledge of firmographic data is desirable but training will be provided if necessary.
Duration of the project:
To apply, please send a CV and a cover letter to Lorcan Mac Manus, firstname.lastname@example.org.