At a Glance
- Tasks: Deliver impactful Marketing Mix Modelling projects and collaborate with clients on strategy.
- Company: Dynamic global media and marketing analytics business with a strong reputation.
- Benefits: Hybrid work model, strong leadership support, and opportunities for professional growth.
- Other info: Join a rapidly growing team with a collaborative culture and exciting projects.
- Why this job: Shape the future of data science while solving real-world marketing challenges.
- Qualifications: Experience in Marketing Mix Modelling and proficiency in Python.
The predicted salary is between 35000 - 45000 £ per year.
This is an exciting opportunity to join a growing data science function at a pivotal stage of its development. You will play a key role in delivering Marketing Mix Modelling (MMM) projects for well-known clients, combining hands-on technical work with exposure to strategic decision-making. With strong backing from leadership and active hiring across the team, this role offers genuine scope to shape how data science is delivered in a high-impact, client-facing environment.
They are a global media and marketing analytics business focused on understanding what truly drives profit. Founded by a technically minded leadership team, they have scaled internationally and built a strong reputation for combining experimentation, proprietary tools, and data science to inform marketing performance. They are now investing heavily in building out their UK data science capability, bringing work in-house and creating a collaborative, high-performing team. This growth phase offers the opportunity to contribute to both client delivery and the evolution of the function.
- Deliver end-to-end Marketing Mix Modelling projects using frameworks such as Meridian, Robyn, or PyMC
- Own key stages of the modelling process, including data preparation, model development, validation, and scenario analysis
- Work directly with stakeholders to support strategy, media planning, and performance optimisation
- Contribute to multiple live projects simultaneously, balancing hands-on technical work with client interaction
- Support the ongoing development of data science best practices and modelling approaches
Strong commercial experience in Marketing Mix Modelling - experience building the models from scratch. Proficiency in Python and experience working with open-source MMM frameworks such as Meridian, Robyn, or PyMC. Ability to assess model quality and clearly communicate findings to non-technical audiences. Exposure to marketing analytics, attribution, or media effectiveness projects is highly beneficial.
Opportunity to join a rapidly growing data science team with strong leadership support. If you are interested in applying your data science expertise to solve real-world marketing challenges in a growing team, please get in touch to learn more.
StudySmarter Expert Advice🤫
We think this is how you could land Econometrician - Contract in London
✨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 Harnham!
✨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 Econometrician - Contract at Harnham.
✨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 Harnham.
✨Apply Directly through Our Website
When you find a suitable opening like Econometrician - Contract at Harnham, 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 Econometrician - Contract in London
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 Harnham, 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 Harnham. 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 Harnham
✨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 Harnham!
✨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.
