Econometric Data Scientist

Are you a skilled Econometrics Data Specialist looking for an exciting opportunity? Join Arla Foods, the UK's leading dairy company, as we strive to become one of the most recognized and trusted food companies in the country. With a wide range of renowned brands in our portfolio, including Lurpak, Arla Cravendale, Starbucks Ready to Drink, Arla Skyr, and Yeo Valley, we are dedicated to bringing innovative dairy products to the market. As a dairy cooperative, we prioritize our farmers and their values in every decision we make. Our commitment to sustainability sets us apart in the food production industry.

We are currently seeking an Econometric Modelling Specialist to join our thriving Digital Marketing Function. In this role, you will play a key part in driving Arla's marketing output by conducting, developing, and optimizing our ROI agenda. Your expertise will help ensure that our content resonates with consumers and guide resource allocation based on past performance.

Key Responsibilities:

• Conduct econometric modelling across categories and brands to deliver valuable insights on optimal budget allocation across touchpoints, timing, and weighting.
• Champion a data-driven approach, prioritizing data and analyses to maximize the value of all media initiatives.
• Support UK marketing budget allocation projects, providing insights on optimal total media budget allocation across categories, brands, and markets.
• Drive portfolio media budget allocation projects for the UK Marketing department, delivering insights on how to optimize budget allocation across brands in the UK.
• Contribute to specific media/budget plans and overall media/budgeting guidelines.
• Support Arla's ROI agenda.
   

Experience:

• We are seeking someone with a strong data science background, experienced in Mixed Media Modelling, and guiding marketing budget/investment decisions using performance data.
• Proficiency in working with data sets, including experience with Kantar and Nielsen, and manipulating other data sources.
• Familiarity with modelling platforms such as StrataQED, etc.
• Demonstrated experience presenting findings to leadership teams and driving recommendations based on performance data.
• Excellent communication skills and the ability to build strong relationships with internal and external stakeholders.