Do you learn best through reverse-engineering? Do you know how web pages work? Are you interested in becoming a hero within a team of existing heroes? If so we could use you to help us:
investigate varied websites architectures by reverse engineering the underlying communication and data flow
build efficient web mining robots (sprider, bots, scrapers) that will stand the test of time
research and design tools and processes to optimize the day-to-day work and data platform
cooperate with the Data Quality and Operations team on overcoming challenges related to efficient robot maintenance
You will be working in the Web Mining team which is a part of the Data Factory function of UBS Evidence Lab. Our job is to build solutions to automatically collect any necessary data. We are creating our own Agile framework to keep the organization scalable and maintain good environment for continuous optimization. The broader Data Factory team specializes in various data related techniques including web harvesting, data cleansing and enrichment.
UBS Evidence Lab is led by visionaries and our culture is like a start-up (without all of the risk). Our unique data-driven approach to investment research is revolutionizing the industry.
You can learn more about Evidence Lab here.
Your experience and skills
You have:
knowledge of web client-server architecture interaction including HTTP, JSON, REST
web development experience including HTML/ CSS, XPATH, DevTools/Firebug
practical understanding of JavaScript
experience with Python or any other popular scripting language
practical experience in working with SQL or NoSQL databases
willingness to propose new ideas and implement innovative solutions
You are:
full of energy and able to persevere through technical issues
a team player willing to learn / share solutions and best practices from your colleagues
able to think outside of the box and solve abstract, ill-defined problems
continuously pursuing self-improvement
efficient English speaker/writer
职能类别: 软件工程师 数据库工程师/管理员
关键字: web data mining
联系方式
上班地址:上海市浦东新区花园石桥路33号3701
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