Marketing Analytics Manager - Lead Data Team (Hybrid)

Marketing Analytics Manager - Lead Data Team (Hybrid)

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Wolt

At a Glance

  • Tasks: Lead a team of Data Scientists to revolutionise marketing strategies and drive impactful decisions.
  • Company: Join Wolt, a dynamic company at the forefront of marketing analytics.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Be part of a talented team and shape the future of marketing analytics.
  • Why this job: Tackle exciting data challenges and make a real difference in marketing initiatives.
  • Qualifications: Strong leadership and project management skills with effective communication abilities.

The predicted salary is between 60000 - 80000 £ per year.

Wolt is looking for an experienced Analytics Manager to join our team in London. In this role, you will revolutionize our marketing strategies, defining analytics roadmaps and guiding key business decisions. You’ll lead a talented team of Data Scientists, ensuring innovative marketing initiatives deliver measurable impact.

To succeed, you’ll need strong leadership, project management skills, and the ability to communicate effectively with cross-functional teams. Join us to tackle interesting data challenges and create a significant impact at Wolt.

Marketing Analytics Manager - Lead Data Team (Hybrid) employer: Wolt

Wolt is an exceptional employer that fosters a dynamic and innovative work culture in the heart of London. With a strong emphasis on employee growth, we provide ample opportunities for professional development and collaboration within a talented team. Our hybrid work model ensures flexibility while tackling exciting data challenges that drive meaningful impact in the marketing landscape.

Wolt

Contact Details:

Wolt Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Marketing Analytics Manager - Lead Data Team (Hybrid)

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 Wolt!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Marketing Analytics Manager - Lead Data Team (Hybrid) at Wolt.

Leverage Professional Networks

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 Wolt.

Apply Directly through Our Website

When you find a suitable opening like Marketing Analytics Manager - Lead Data Team (Hybrid) at Wolt, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Marketing Analytics Manager - Lead Data Team (Hybrid)

Leadership
Project Management
Data Analysis
Communication Skills
Team Management
Strategic Thinking
Cross-Functional Collaboration

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 Wolt, 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 Wolt. 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 Wolt

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 Wolt!

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.