At a Glance
- Tasks: Lead a team to deliver innovative measurement solutions for advertisers.
- Company: Join Google, a leader in tech innovation and collaboration.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic role with opportunities for cross-functional collaboration and career advancement.
- Why this job: Make a real impact in the advertising tech space while mentoring others.
- Qualifications: Experience in product deployment and data science, with strong leadership skills.
The predicted salary is between 70000 - 90000 £ per year.
Google is seeking a senior Measurement Product Deployment Engineer and Data Scientist to lead a high-performing team within gTech Ads. You will mentor PDEs and data scientists, drive cross-functional collaboration with Sales, Product, and Engineering, and deliver complex measurement solutions for advertisers.
Based in London, you will identify growth opportunities, coordinate technical implementations, and help scale solutions across a distributed organization while maintaining a strong client.
Measurement Product & Deployment Lead – Ads Tech 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.
StudySmarter Expert Advice🤫
We think this is how you could land Measurement Product & Deployment Lead – Ads Tech
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Google!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Google.
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We think you need these skills to ace Measurement Product & Deployment Lead – Ads Tech
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Google, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Google. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Google!
✨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.
