At a Glance
- Tasks: Lead high-impact projects, mentor junior data scientists, and build innovative data products.
- Company: Join Google, a global leader in technology and innovation.
- Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a focus on collaboration and data integrity.
- Why this job: Make a real impact on e-commerce and AI initiatives that serve billions worldwide.
- Qualifications: 10 years of analytics experience or 5 years with a Master's degree in a quantitative field.
The predicted salary is between 80000 - 100000 £ per year.
Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.
Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Experience taking projects from ambiguous concepts to finished, high-quality data products within a cross-functional unit. Experience navigating e-commerce or marketplace data, including an understanding of merchant behaviour and consumer life-cycles. Experience in SQL, with the ability to build maintainable data workflows and statistical models.
About the job: Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. As a Staff Data Scientist, you are a lead architect for the mission to build scalable, commercially focused, and machine consumable data products and insights that simplify problems and drive outcomes for merchants and consumers. You bridge the gap between complex datasets and business goals, across high-impact, cross-functional teams. Operating with high autonomy, you solve the organisation’s most unclear and meaningful problems rather than being tied to a single product silo. You are a leader in the analytics community, ensuring work is reliable and high-quality to deliver lasting solutions. As a Technical Lead, you are accountable for others in defining valuable goals and ensuring projects deliver clear business results. You act as a key partner to Engineering and Product leaders, helping shape the direction of our AI data products within our "one-team" model. We take pride in our ability to make complex things simple and tell clear stories through data. As a senior leader in this team, you will have a global impact, contributing to Google’s high-profile agentic AI initiatives.
Users come first at Google. Nowhere is this more important than on our Advertising and Commerce team: we believe that ads and commercial information can be highly useful to our users if that information is relevant to what our users wish to find or do. Advertisers worldwide use Google Ads to promote their products; publishers use AdSense to serve relevant ads on their website; and businesses around the world use our products (like Google Shopping, and Google Wallet) to support their online businesses and bring users into their offline stores. We are constantly innovating to deliver the most effective advertising and commerce opportunities of tomorrow.
Responsibilities:
- Technical Leadership and Solving Ambiguity: Lead high-stakes projects with unclear goals, mentoring junior data scientists to define high-value problem statements and deliver measurable business impact.
- Scalable Product Innovation: Build commercially focused, self-serve data products and AI-automated insights that move beyond traditional dashboards for merchants and shoppers.
- Strategic Advising: Consult with Engineering and Product leaders, providing data-driven perspectives on product direction and identifying new opportunities grounded in data.
- Metric Design and Infrastructure Advocacy: Define key metrics and attribution mechanisms while advising data engineering on infrastructure optimisations for "machine-consumable" insights.
- Radical Transparency: Advocate data integrity across product areas, reducing organisational paralysis through clear, data-backed conversations with senior leadership.
Staff Product Data Scientist, Google Shopping in London employer: Google
At Google, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to innovate and excel. As a Staff Product Data Scientist, you will have the opportunity to lead high-impact projects, mentor junior team members, and contribute to groundbreaking AI initiatives that shape the future of e-commerce. With a commitment to employee growth and a focus on collaboration across diverse teams, Google offers a unique environment where your analytical skills can drive meaningful change for users worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Product Data Scientist, Google Shopping in London
✨Tip Number 1
Network like a pro! Reach out to current or former Googlers on LinkedIn and ask for informational chats. It’s a great way to get insider info about the role and show your genuine interest.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Make sure you can confidently discuss your experience with SQL, Python, and statistical analysis. Practice coding challenges to keep your skills sharp!
✨Tip Number 3
Showcase your problem-solving abilities! Be ready to share examples of how you've taken ambiguous projects and turned them into successful data products. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨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, it shows you’re serious about joining the team at Google.
We think you need these skills to ace Staff Product Data Scientist, Google Shopping in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with analytics and coding in your application. We want to see how you've used tools like Python, R, or SQL to tackle real-world problems. Don't just list your skills; tell us how you've applied them!
Tell a Story with Data:We love data-driven narratives! When you describe your past projects, focus on how you turned complex datasets into actionable insights. Share specific examples of how your work made a difference in previous roles.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your key achievements stand out. Remember, we’re looking for high-quality applications that reflect your best work!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Google
✨Know Your Numbers
Make sure you brush up on your statistical analysis skills and coding languages like Python, R, and SQL. Be ready to discuss specific projects where you've used these skills to solve complex problems, as this will show your practical experience and understanding of the role.
✨Tell a Compelling Story
Prepare to weave narratives from your data insights. Think about how you've transformed ambiguous concepts into clear, actionable outcomes in past projects. This will demonstrate your ability to communicate effectively with cross-functional teams and highlight your strategic advising skills.
✨Showcase Your Leadership
As a Staff Data Scientist, you'll be expected to lead and mentor others. Be prepared to share examples of how you've guided junior team members or led high-stakes projects. Highlight your experience in navigating ambiguity and delivering measurable business impact.
✨Understand the E-commerce Landscape
Familiarise yourself with e-commerce and marketplace data, including merchant behaviour and consumer life-cycles. Being able to discuss trends and insights in this area will show that you understand the broader context of your work and can contribute to Google's mission effectively.
