At a Glance
- Tasks: Analyse data to solve business challenges and develop impactful recommendations.
- Company: Join Google, a leader in innovation and technology.
- Benefits: Competitive salary, diverse culture, and opportunities for growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact by solving complex problems with data.
- Qualifications: Master's degree and experience in analytics, coding, and marketing data.
The predicted salary is between 70000 - 90000 £ per year.
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with Generative AI, Large Language Models (LLMs), or Machine Learning.
Preferred qualifications:
- 7 years of business analytics experience building big data pipelines, schemas and data sets, specifically 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 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 and experience in root cause analysis to ensure that problems are solved at tactical level.
- Experience with marketing data.
About the job:
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.
Responsibilities:
- Develop evaluation frameworks for models, new metrics, and investigate anomalies.
- 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.
- Develop QA processes to ensure that data is checked and validated before release to internal teams and work with stakeholders to incorporate feedback ensuring that systems, tooling and datasets are usable for defined deliverables.
- Develop detailed delivery plans and communications for key deliverables to keep relevant stakeholders informed.
- Work with internal and external stakeholders to implement and update processes where necessary.
- Create “self-serve” capabilities within the team for non-technical users and work with the Analytics and Data Science teams to create complex ad hoc datasets where self-service is infeasible.
Senior Business and Marketing Data Scientist employer: Google
At Google, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. As a Senior Business and Marketing Data Scientist in London, you'll have access to cutting-edge technology and the opportunity to collaborate with cross-functional teams on impactful projects. With a strong emphasis on employee growth, we offer continuous learning opportunities and a culture that values diverse perspectives, making it an exceptional place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Business and Marketing Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and analytics. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to data science and marketing analytics. We recommend using the STAR method to structure your answers – it’s all about showing how you’ve tackled challenges.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Business and Marketing Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Business and Marketing Data Scientist role. Highlight your experience with analytics, coding, and any relevant projects that showcase your skills in data pipelines and marketing data.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background aligns with Google's mission. Don't forget to mention your experience with Generative AI and Machine Learning if applicable!
Showcase Your Technical Skills:Be sure to list your technical skills prominently, especially your proficiency in Python, R, SQL, and any reporting tools like Tableau or Power BI. We want to see how you can leverage these skills to solve business problems.
Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s straightforward and ensures your application goes directly to the right team. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Google
✨Know Your Data Inside Out
As a Senior Business and Marketing Data Scientist, you’ll need to demonstrate your expertise in data analysis. Brush up on your knowledge of big data pipelines, schemas, and the specific tools mentioned in the job description like SQL and Python. Be ready to discuss how you've used these skills to solve real business problems.
✨Showcase Your Project Management Skills
This role involves working with cross-functional teams and managing projects. Prepare examples of past projects where you successfully collaborated with different stakeholders. Highlight your ability to develop detailed delivery plans and communicate effectively to keep everyone informed.
✨Prepare for Technical Questions
Expect technical questions related to Generative AI, LLMs, and machine learning. Review key concepts and be prepared to explain how you’ve applied them in your previous roles. Practising coding challenges or data analysis scenarios can also give you an edge.
✨Communicate Your Insights Clearly
You’ll need to persuasively communicate your recommendations to senior executives. Practice summarising complex data insights into clear, actionable recommendations. Use storytelling techniques to make your points relatable and impactful during the interview.
