Posted May 24, 2016 - Requisition No. 49862
We work on discovering connections, insights and workflows in a sea of financial and news data. Our hope is to use inherent attributes of data such as co-occurrence in contexts (rather than business rules) for prediction, contextualization and pervasive recommendation tasks to connect our users to the information they seek. To do this well and at scale, we need to build a robust distributed data science platform. Our infrastructure will support ingestion, processing and machine learning-powered analysis of a vast amount of disparate data.
We need your help in designing and engineering this infrastructure. We are a small team bullish on open source (with active contribution in Solr, Maven, Chef and Hadoop communities). Due to our team size, the relative youth of the project and a full stack ownership model, you will work with an uncommon depth and breadth of technologies and have the opportunity to shape a platform that will be critical to companies in the years to come.
If this sounds like you, apply! You can also check out our Bloomberg Labs Website (http://www.bloomberglabs.com/data-science/) to learn more about how our data scientists apply methods from machine learning, natural language processing and search to solve complex problems across the company.