Posts Tagged ‘JP Morgan’

Semantic Web Jobs: JP Morgan Chase

JPMorganJP Morgan Chase is looking for a Hadoop Data Architect Lead in Brooklyn, NY. According to the post, “The Risk ODS Storage Re-platforming group is seeking a ‘Hands On’ Build Manager with Core Java development leadership and production delivery experience to join our system’s data distribution platform team. Potential Candidates MUST have experience with and are enthusiastic about developing all areas of Middle-Tier and Back-end system programming. The responsibilities of this position include but are not limited to: Writing large scale Java programs in pure Core Java to facilitate both real-time and batch processing. All processes will be deployed to Unix/Linux environments, therefore a deep working understanding of Unix/Linux is required.” Read more

Semantic Web Jobs: JP Morgan Chase

JPMorgan

JP Morgan Chase is looking for a Vice President / Manager of Metadata Business Analysis in Brooklyn, NY. According to the post, “Risk Technology provides risk measurement and reporting services to JPMC. We measure market risk, credit risk and other aspects of financial risk, provide stress-testing services for the firm’s trading portfolios and produce risk reports at numerous organizational levels, which are reviewed by top-level management every day. The Cross Risk Information Strategy program is chartered to re-engineer multiple dimensions of Risk Technology Architecture and Infrastructure to improve accuracy, consistency, and granularity across Risk, Capital, and Regulatory Reporting. The team is new and highly motivated. ” Read more

Financial Services In The Spotlight At Sentiment Analysis Symposium

The financial services sector was in focus at this week’s Sentiment Analysis Symposium in New York City, which is organized and produced by Alta Plana Corp. and its founder, Seth Grimes.  Take, for example, the presentation by Rich Brown, head of Elektron Analytics at Thomson Reuters, who disclosed that the company is about to launch market response indicators in support of its Thomson Reuters News Analytics system for the financial community. That product this week also won The Technical Analyst’s 2012 award for best news analytics software.

With its software, originally discussed here, qualitative, unstructured information is turned into a quantitative data set allowing users – machines and humans – to quickly analyze thousands of news stories in less time than it takes to read a single headline, as Thomson Reuters describes it. It uses natural language processing technology to get to the end game, which is to forecast financial market response from news and social media sentiment. Some 82 fields of metadata come into play for automating the analysis of news content. That encompasses sentiment down through to the degree of positive, negative or neutral expressions and how individual companies mentioned in a piece fare in those respects – rather than just the tone of the piece at large. “The computational linguistics system measures the author’s tone as positive or negative on any given entity, which is important and the harder part of it,” Brown said. Other fields include, for example, relevance, genre, intensity of news flow, and more.

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