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For Companies At a Glance
- Tasks: Lead end-to-end modelling projects and deliver insightful analysis.
- Company: Join a fast-growing agency helping brands understand performance through analytics.
- Benefits: Enjoy hybrid work options and a culture of continuous improvement.
- Why this job: Be part of a collaborative team making a real impact in marketing effectiveness.
- Qualifications: 2-3 years of MMM experience and strong skills in R or Python required.
- Other info: Opportunity to work with top brands in the FMCG sector.
The predicted salary is between 36000 - 60000 £ per year.
MBN's client, an established and fast-growing marketing effectiveness agency on a mission to help brands truly understand what’s driving performance — and how to do better. Our work is grounded in rigorous analytics and trusted by some of the world’s most recognisable brands. As demand for our services grows, particularly within the FMCG space, we’re looking for a skilled Econometrician / Data Scientist with hands-on experience in Marketing Mix Modelling (MMM) to join our team.
About the Role
You’ll take ownership of end-to-end modelling projects — from data ingestion through to modelling, validation, and producing client-ready outputs. While direct client interaction is limited in this role, your work will be at the core of delivering meaningful insights and commercial value. You’ll work alongside a collaborative, ego-free team that values openness, technical rigour, and continuous improvement.
What You’ll Be Doing
- Lead MMM modelling projects: from data prep, exploration, and variable selection through to final model delivery
- Build clear, insightful analysis decks for internal teams and client presentations
- Apply econometric techniques including regression modelling, adstock, saturation, lag structures, and more
- Continuously improve processes as part of a company that invests heavily in technical development
What We’re Looking For
Must-haves:
- 2–3 years of hands-on MMM experience
- Strong modelling skills in R, Python, or similar statistical tools
- Confident handling, cleaning, and transforming large datasets
- Analytical mindset with a sharp eye for detail
- Ability to work independently on modelling tasks from start to finish
Nice-to-haves:
- Familiarity with FMCG data and media mix variables (TV, digital, OOH, promotions, etc.)
- Understanding of FMCG dynamics like seasonality, product cannibalisation, and baseline shifts
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Analyst
Industries: IT Services and IT Consulting
Econometrician/Data Scientist employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Econometrician/Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in Marketing Mix Modelling (MMM) and econometric techniques. This will not only enhance your understanding but also demonstrate your commitment to staying updated in a rapidly evolving field.
✨Tip Number 2
Network with professionals in the marketing effectiveness and data science sectors. Attend relevant webinars, workshops, or meetups to connect with industry experts and gain insights that could give you an edge during interviews.
✨Tip Number 3
Showcase your hands-on experience with R or Python by working on personal projects or contributing to open-source initiatives. This practical experience can be a great conversation starter and highlight your technical skills.
✨Tip Number 4
Prepare to discuss specific examples of how you've handled large datasets and applied econometric techniques in past roles. Being able to articulate your thought process and results will impress potential employers.
We think you need these skills to ace Econometrician/Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 2-3 years of hands-on experience in Marketing Mix Modelling (MMM). Emphasise your skills in R, Python, or other statistical tools, and showcase any relevant projects that demonstrate your modelling capabilities.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about econometrics and data science. Mention specific examples of how you've successfully handled large datasets and applied econometric techniques in previous roles, particularly in relation to FMCG.
Showcase Your Analytical Skills: During the application process, be prepared to discuss your analytical mindset. Provide examples of how you've approached complex modelling tasks independently and the impact your work had on previous projects or clients.
Highlight Continuous Improvement: Mention any initiatives you've taken to improve processes or methodologies in your past roles. This aligns with the company's value of continuous improvement and shows that you are proactive in your professional development.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with R, Python, or other statistical tools. Highlight specific projects where you applied econometric techniques like regression modelling and adstock, as this will demonstrate your hands-on expertise.
✨Understand the FMCG Landscape
Familiarise yourself with FMCG data and media mix variables. Being able to discuss seasonality, product cannibalisation, and baseline shifts will show that you understand the industry context in which you'll be working.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical mindset and problem-solving abilities. Be ready to walk through your thought process on how you would approach a modelling task from start to finish, showcasing your independence and attention to detail.
✨Emphasise Collaboration and Continuous Improvement
Since the role involves working within a collaborative team, share examples of how you've contributed to team projects. Discuss any initiatives you've taken to improve processes, as this aligns with the company's value of continuous improvement.
