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- Tasks: Develop econometric models and analyse marketing data for actionable insights.
- Company: Global lifestyle brand focused on enhancing marketing effectiveness.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact on global marketing strategies.
- Qualifications: Strong Python and SQL skills, with experience in MMM tools.
- Other info: Collaborative environment with cross-functional teamwork and stakeholder presentations.
The predicted salary is between 36000 - 60000 £ per year.
A global lifestyle brand is seeking an experienced MMM Data Scientist to enhance its global marketing effectiveness. This role involves developing and maintaining econometric models, analyzing marketing data, and providing actionable insights. You will collaborate with cross-functional teams and present findings to stakeholders, all while working in a hybrid model of 2-3 days a week in London.
The ideal candidate has strong Python and SQL skills and familiarity with MMM tools in marketing contexts.
MMM Data Scientist: Marketing Analytics & ROI Insights employer: FRESHMINDS
Contact Detail:
FRESHMINDS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MMM Data Scientist: Marketing Analytics & ROI Insights
✨Tip Number 1
Network like a pro! Reach out to professionals in the marketing analytics space on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your econometric models and analyses. Use real-world examples to demonstrate how your insights have driven marketing effectiveness, making it easier for employers to see your value.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss specific projects where you’ve used these tools to derive actionable insights. Practice common interview questions related to MMM and marketing analytics.
✨Tip Number 4
Don’t forget to apply through our website! We often have exclusive listings that might not be found elsewhere. Plus, it shows you’re genuinely interested in joining our team and makes it easier for us to connect with you.
We think you need these skills to ace MMM Data Scientist: Marketing Analytics & ROI Insights
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you’ve used these tools in real-world scenarios, especially in marketing contexts.
Tailor Your Application: Don’t just send a generic CV and cover letter. Tailor your application to reflect the specific requirements of the MMM Data Scientist role. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and insights without wading through unnecessary fluff.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at FRESHMINDS
✨Know Your Econometrics
Brush up on your econometric modelling skills before the interview. Be ready to discuss specific models you've developed or worked with, and how they impacted marketing effectiveness. This will show your expertise and understanding of the role.
✨Showcase Your Data Skills
Prepare to demonstrate your proficiency in Python and SQL. You might be asked to solve a problem or analyse a dataset on the spot, so practice coding challenges related to data analysis and manipulation to impress your interviewers.
✨Understand the Brand
Research the global lifestyle brand thoroughly. Familiarise yourself with their marketing strategies and recent campaigns. This knowledge will help you tailor your answers and show that you're genuinely interested in contributing to their success.
✨Prepare for Cross-Functional Collaboration
Think of examples where you've successfully collaborated with different teams. Be ready to discuss how you communicated complex data insights to non-technical stakeholders, as this is crucial for the role and will highlight your teamwork skills.
