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- Tasks: Lead data modelling projects and create insightful presentations for clients.
- Company: Join a fast-growing marketing effectiveness agency that prioritises its people.
- Benefits: Enjoy hybrid working, gym membership, pension, and yearly bonuses.
- Why this job: Make a real impact in a supportive culture where your ideas matter.
- Qualifications: 2-3 years of experience in Marketing Mix Modelling; strong skills in R or Python.
- Other info: Refer friends for rewards and be part of a diverse team.
London (Hybrid working 3 office days per week) Salary DOE £40,000-£45,000
Additional Benefits: Gym Membership, Pension and yearly bonus
We are excited to be hiring for a unique opportunity to join a fast-growing, independent marketing effectiveness agency that genuinely puts its people first. This is a chance for someone who wants to be a bigger fish in a smaller sea to step into a role where you can truly make your mark, have real influence, and accelerate your career growth as we continue to scale. With a loyal and diverse client base, and a culture built on support and empowerment, you will be part of a team where your ideas are heard and your impact is recognised.
We are looking for a motivated and capable Econometrician / Data Scientist with 2-3 years of hands-on experience in Marketing Mix Modelling (MMM). Experience within the FMCG sector would be a bonus, but it is not essential.
Roles and Responsibilities- This role is well-suited for candidates who have a strong analytical mindset and prefer working behind the scenes with data.
- Leading the modelling process from briefing, data exploration, and variable selection through to model building, interpretation, and being involved in the presentation of results (interim and final debriefs will be presented by the Account Director).
- Creating clear and insightful output decks for both internal stakeholders and client presentations.
- Strong econometric modelling skills using tools such as R, Python, or other statistical software packages (e.g., EViews, SAS).
- Experience with model validation, diagnostics, and performance metrics.
- Ability to handle large datasets, clean and transform raw data, and apply advanced statistical techniques such as regression, lag structures, adstock, saturation, and interaction effects.
- The successful candidate will be expected to take full ownership of modelling projects, from raw data ingestion through to final model delivery and client-ready outputs, with minimal supervision.
If this sounds like you then please apply!
Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.
Econometrician / Data Scientist employer: Datatech
Contact Detail:
Datatech 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 econometrics and data science, especially in Marketing Mix Modelling. This will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the marketing effectiveness sector. Attend relevant meetups or webinars to connect with industry insiders who might provide insights or even referrals for the role.
✨Tip Number 3
Prepare to discuss specific projects where you've applied econometric modelling techniques. Be ready to explain your thought process, the tools you used, and the impact of your work on previous projects.
✨Tip Number 4
Showcase your ability to communicate complex data insights clearly. Practice presenting your findings as if you were addressing both technical and non-technical audiences, as this is crucial for client presentations.
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 experience in econometric modelling and data science. Focus on relevant skills such as proficiency in R or Python, and any experience with Marketing Mix Modelling (MMM) or the FMCG sector.
Craft a Compelling Cover Letter: Write a cover letter that showcases your analytical mindset and your ability to handle large datasets. Mention specific projects where you've taken ownership of modelling processes and how your contributions made an impact.
Highlight Relevant Experience: In your application, emphasise your hands-on experience with statistical software packages and your familiarity with model validation and diagnostics. Use concrete examples to demonstrate your skills.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is crucial for a role that involves data analysis.
How to prepare for a job interview at Datatech
✨Showcase Your Analytical Skills
As an Econometrician/Data Scientist, your analytical mindset is crucial. Be prepared to discuss specific projects where you've applied econometric modelling techniques, especially in Marketing Mix Modelling. Highlight your experience with tools like R or Python and how you've used them to derive insights from data.
✨Prepare for Technical Questions
Expect questions that test your understanding of statistical concepts and methodologies. Brush up on model validation, diagnostics, and performance metrics. Be ready to explain complex ideas in simple terms, as you may need to present findings to non-technical stakeholders.
✨Demonstrate Ownership of Projects
The role requires taking full ownership of modelling projects. Share examples of how you've managed projects from start to finish, including data cleaning, transformation, and final delivery. Emphasise your ability to work independently and make decisions with minimal supervision.
✨Engage with the Company Culture
This agency values a supportive and empowering culture. During the interview, express your enthusiasm for being part of a team where ideas are heard. Discuss how you can contribute to this environment and how your values align with theirs, particularly in terms of collaboration and innovation.
