Data Analyst, Content Generation and Automation
Bloomberg’s Global Data division is creating a Content Generation and Automation team that seeks to build a team of analysts with strong technical skills and domain expertise in Financial Markets. This group is responsible for idea generation, testing, validation, and development of the technical infrastructure to automatically create and deliver impactful content. Content and data generated by this team will be used for automated news, events, and core product that will support company-wide initiatives including Events Generation, Key Insights, and News Automation. Leverage your understanding of what drives the financial markets to identify opportunities for automated content generation, while working closely with partners across departments to implement automated content. To achieve this, you will utilize your technical and market knowledge to design, template and validate potential market moving events using our corpus of data in conjunction with back-testing and anomaly detection techniques, to ensure the events impact.
In close collaboration with stakeholders, development teams, data teams, and client, you will turn these content ideas into reality and drive integration with core product, news, and data using our proprietary technology stack. Lead projects aimed at generating content to support News & Core Product. Leverage your strong technical skills to build automated content and back-testing models that will support the future development of new content and events. Identify opportunities to improve data quality and develop solutions. Demonstrated knowledge of Python with proven experience leveraging to perform data analysis, process enhancements and automation, etc.
Ability to analyze large quantities of data through data analysis tools and an ability to interact and pull data from different types of databases and systemsDrive and motivation to work independently as well as with large groups of stakeholders. Experience working with Bloomberg data to build tools, templates, or models by using tools such as BQL/BQUANT, Microsoft Excel, R, etc.
Reuters is the latest large news agency to embrace content automation – TechCrunch
Reuters is the latest major news agency to embrace content automation. Reuters isn’t replacing human reporters and editors with software and self-flying cameras quite yet. The news organization has struck partnerships with Graphiq Inc. and Wibbitz Ltd., to automate the creation of simple graphics and video clips, respectively, to run alongside relevant, human-reported Reuters news content on the third party sites that pay for and run it. Graphiq Inc.
based in Santa Barbara, Calif., has integrated its free-to-use visualizations platform with Reuters News Agency to make the simple graphs and visualizations it creates in thousands of Reuters articles wherever they run on 3rd party sites. According to Graphiq GM Alex Rosenberg, Graphiq works with hundreds of publishers, including TechCrunch and now Reuters, to put dynamically generated infographics into articles. The company’s systems ingest data from public and private sources to create instant infographics. Graphiq generates revenue when readers of a Reuters or other news article see and click on a graphic, and visit the company’s own website which is ad-supported. Tel Aviv-based Wibbitz uses natural language processing and algorithms to scan text captions and news articles to understand what a story is basically about.
Its software-as-a-service then automatically summarizes a story, can create a voiceover or script for a story, and packages up video clips, photos and infographics available within a publisher’s platform or Wibbitz’s own, to generate a ready to publish video version of a story, in minutes. She said new technologies are constantly evaluated by Reuters by a team there called the Emerging Technology Group which is separate from the news agency. AP uses software to automate local sports reporting, and earnings reports. ProPublica has used software to help conduct an investigation into which states are providing, or failing to provide, low-income high school students with the coursework they need to get into and succeed in college.
Automating content creation for docs
Adyen has a team of over 140 developers, with several code commits being made each minute, across more than seven languages, and 25+ products. The great thing about documenting source code is that all information is already present in the code. There are several tools to generate overviews of objects and methods from source code. While JavaDoc-style code references are common documentation sources for developers, they are far from intuitive. Code references needed to be embedded in the docs that describe how to use them, and ideally accompanied by samples/snippets that implement the referenced code.3.
With such a large body of code, finding the relevant changes that affect developers integrating with Adyen was a significant challenge. Phase 1: Use Doxygen to push code to the CMS.Doxygen is a tool that takes annotated/commented source files from code repositories, and generates code references in HTML or an offline reference manual. Whenever Jenkins detects a commit to the code base, it checks out a new copy of the latest version for the specific documentation project. This was a great start in terms of automating the process, but it was no use if we couldn’t ensure that our code snippets and tables weren’t presented clearly. We automatically included macros to further improve the look and feel of our docs including such things as page properties, code blocks, and so on.
This process is now very fast and easy - we simply upload the JSON file of the use case to the code repository, which automatically triggers the whole process to generate a new page on our docs website, with only the information relevant to that specific case.200 pages worth of documentation, which would have previously taken weeks of work to create manually, were generated in 15 seconds flat. This approach is helping us to scale docs and keep our team resources available for bigger projects, while enabling developers integrating with Adyen to be confident in the knowledge that all our code samples and tables are up-to-date.