data scientist

data scientist London, England

Google
Full Time London, England 10.56 - 12.04 GBP Today
Job description

data

Minimum qualifications:

  • Experience in business analytics building big data pipelines, schemas and data sets, within a media data context.
  • Experience using reporting tools (e.g. Tableau, Looker, Power BI) to build business solutions to improve decision making and execution.
  • Experience of data querying languages, statistical programming languages or Machine Learning Models.

Preferred qualifications:

  • Experience of project managing and building data pipelines, schemas and data sets working with both internal and external partners.
  • Experience working with cross-functional teams and stakeholders.
  • Experience of root cause analysis to ensure that problems are solved at both a tactical and strategic level.
  • Experience with marketing data.
  • Experience of working with Cloud technologies.
  • Knowledge of statistical concepts, techniques, and methods.

About the job

This role requires a unique blend of media, statistics, data infrastructure and reporting experience.

On a more day to day basis you will play a strategic and technical role in driving all things marketing data, with a strong focus on digital marketing data pipelines. You will be required to partner with internal teams to scope, build and deliver strategic initiatives. You will own the end-to-end program management and delivery of key initiatives that support analytics, reporting, modeling and optimization projects.

As a Marketing Data Manager you will be seen as an expert within our team on all things that relate to marketing data, data storage, script writing and dev projects. You will maintain a global scope, and while based out of London, will be directly supporting global marketing data projects and will act as a bridge across all regions.

Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems-from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can-changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

Responsibilities

  • Develop QA processes to ensure that data is checked and validated before release to internal teams, as well as developing detailed delivery plans and communications for key deliverables to keep relevant stakeholders informed.
  • Build and maintain data pipelines, dashboards and business scorecards to help organize data from multiple sources into an easy to digest format that meets functional and business needs.
  • Work with stakeholders to incorporate feedback ensuring that systems, tooling and datasets are usable for defined deliverables, as well as working with internal and external stakeholders to implement and update processes where necessary, creating “self-serve” capabilities within the team for non-technical users.
  • Work with the Analytics and Data Science teams to create complex ad hoc datasets where self-service is infeasible, contributing to detailed technical and end-user documentation and training.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

data scientist
Google

goo.gle/3ygdkgv
Mountain View, United States
Sundar Pichai
$10+ billion (USD)
10000+ Employees
Company - Public
Internet & Web Services
1998
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