At a Glance
- Tasks: Lead data science projects, translating business challenges into innovative solutions.
- Company: Join Google’s Marketing Media Lab team and tackle complex business problems.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentorship and team development.
- Why this job: Make a real impact by driving marketing analytics and shaping business strategies.
- Qualifications: Master's degree in a quantitative field and 7 years of analytics experience required.
The predicted salary is between 63000 - 77000 £ per year.
- 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.
- 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.
About The Job
Google's leadership team hand-picks thorny business challenges, and members of Biz Ops 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.
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 .
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Data Science Manager, Marketing employer: Google
Google is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among its employees. With a strong commitment to professional development, team members have access to numerous growth opportunities and resources to enhance their skills. Working remotely in the UK allows for a flexible work-life balance while being part of a globally recognised leader in technology.
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We think this is how you could land Data Science Manager, Marketing
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We think you need these skills to ace Data Science Manager, Marketing
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Google
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
