Data Science Manager, Marketing

On-site in London·Added 19 days ago (last checked 1 Oct)

Google

168 open roles

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Overview

Requirements

Work on-site in London
No relocation package mentioned.
Have 7+ years of experience
Senior-level role.

Skills

Requirements

Minimum qualifications:

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Preferred qualifications:

2 years of experience managing an Analytics or Data Science team, including prioritisation, roadmapping, coaching and performance management.
Experiences with experimental design and supervised/unsupervised ML approaches for regression and classification tasks.
Experience of root cause analysis to ensure that problems are solved at both a tactical and strategic level.
Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling .
Understanding of Bayesian approaches and modeling frameworks.
Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross functional stakeholders.

The role

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

As a Data Science Manager in the Marketing Media Lab team, you will lead projects, translating business problems into investigative solutions and you will guide your team to implement data science solutions, improve data, develop metrics, and build models for business insights. You will also foster knowledge sharing and develop your team's talent.

You will play a strategic and technical role in driving all things media, marketing, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google's media investment and the industry's toughest issues, at a global scale.

Responsibilities

Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science.
Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors of performance and critical drivers for a successful media plan.
Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.
Partner with internal teams to scope, build and deliver strategic initiatives driving all things marketing data, with a strong focus on digital marketing data pipelines.
Lead and develop the team, taking ownership of team roadmapping, initiative prioritization, individual coaching, and ongoing performance management.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.