Global Data - Data Scientist Global Data - Data Scientist …

Bloomberg
in London, England, United Kingdom
Permanent, Full time
Last application, 17 Jun 19
Competitive
Bloomberg
in London, England, United Kingdom
Permanent, Full time
Last application, 17 Jun 19
Competitive
Global Data - Data Scientist
Bloomberg runs on data, and in the Global Data team we're responsible for acquiring it and providing it to our clients. We collect, analyse, process and publish the data which is the backbone of our iconic Bloomberg Terminal- the facts and figures which ultimately move the financial markets. We apply problem-solving skills to identify innovative workflow efficiencies and we implement technology solutions to enhance our systems, products and processes- and all this while providing platinum customer support to our clients.

The Role:
Data Scientists use statistical and machine learning methods to innovate solutions in major focus areas like data quality and automation. This requires developing production-grade machine learning models or ad-hoc analysis in order to demonstrate tangible business impact. They are typically aligned with one or more data products and are expected to acquire subject matter expertise, as needed. Finally, Data Scientists contribute to Global Data's overall analytical strategy and train and mentor other employees throughout the business unit.

We'll trust you to:
  • Identify and build statistical and machine learning solutions to improve Bloomberg's data quality and operational efficiency
  • Use analytical methods to innovate new data products
  • Write production-level code
  • Apply problem-solving skills to create flexible and innovative technology solutions that can be re-used across products
  • Gather requirements, develop project plans, monitor progress, and communicate with stakeholders throughout the development lifecycle
  • Collaborate with Engineering to implement analytical solutions in production systems
  • Train and mentor Data Analysts in analytical methods

You'll need to have:
  • An MA/MS degree or higher in a quantitative field or at least two years of demonstrable relevant work experience
  • Experience applying a range of statistical and machine learning methods to real-world problems
  • Applied proficiency with one or more programming/scripting languages (e.g. Python, Java, Scala, C++)
  • Familiarity with software engineering best practices, including testing and version control
  • Strong aptitude for problem solving, particularly to modify and enhance processes and workflows
  • Project management skills: ideation, prioritization, communication, delivery
  • Excellent written and verbal communication skills, especially when explaining technical processes and solutions to business stakeholders and management

We'd love to see:
  • Established presence in virtual development communities such as GitHub, Stack Overflow and HackerRank
  • Exposure to Bloomberg products such as the Professional Service
  • Ability to work independently as well as in a team environment
  • Desire to influence others and lead change
  • Familiarity with the financial markets

Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are! In the meantime feel free to have a look at this:

https://www.bloomberg.com/careers/global-data/

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email access2@bloomberg.net. Alternatively, you can get support from our disability partner EmployAbility, please contact +44 7852 764 684 or info@employ-ability.org.uk.

Opening date: 5th June 2019
Closing date: 3rd July 2019
Compensation: Competitive salary plus benefits

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