Build and own the total GB outlet universe: define what counts as an outlet in each channel, then size and segment it by combining licensed premises data, food business registers, points of interest data, wholesaler and distributor records, and our own field sales data.
Work with Data Science at HQ to design methodologies for estimating the universe and our distribution in channels where no single provider covers the market, including sampling approaches, extrapolation, weighting and stated confidence levels.
Working closely with the REACH Strategy Manager, establish and run a monthly tracking cycle for horizontal distribution: numeric distribution by channel and account type, with clear rules on versioning, restatement and when the universe is re-based.
Validate modelled estimates against ground truth from field audits, wholesaler and distributor sell-out data and customer data, and document known gaps, biases and margins of error openly.
Turn the market read into action: prioritised outlet target lists, white space maps and channel opportunity sizing that field sales and channel teams can work from directly.
Red Bull UK is currently recruiting for a Business Analyst (Reach & On Premise) to be based in London, UK.
The core purpose of this role is to organise and structure our On Premise data assets so that the channel can be reported, analysed, automated and prepared for AI. On Premise data is far more fragmented than the Off Premise: there is no single measurement provider covering the full outlet universe, and coverage is thinnest in exactly the channels we are trying to grow into. This role builds the data foundations that close that gap, creating structured, scalable datasets and automated reporting that make On Premise decision-making faster and better evidenced.
This role also owns the market read behind REACH, our programme to drive horizontal distribution and put Red Bull in outlets where we have never been listed. Sizing the outlet universe channel by channel, establishing where we are and are not present, and tracking horizontal distribution monthly with a methodology that stands up to scrutiny. This groundwork will lead to collaboration with the Reach Strategy Manager, translating commercial questions into structured analytical requirements and taking ownership of delivering a clear and actionable answer.
Alongside the REACH requirements, the role will provide hand-on analytical and reporting support across the Commercial business, investigating performance to answer business questions and continually improve the quality and efficiency of commercial reporting.
This role has a large part to play in both driving strategic business decisions in the long term and tracking performance short term. It has high exposure to multiple departments both locally and at our HQ in Austria, so developing excellent relationships with our internal stakeholders is key.
Every application is reviewed by a member of our recruitment team. We take a people-first approach to hiring, ensuring that every application receives thoughtful consideration
All the responsibilities we'll trust you with:
Translate business questions into data requirements and ensure data assets meet these needs.
Act as a liaison between business users and technical teams (i.e. IT, Data Science at HQ, external data providers).
Work with the Performance Insights team and with On Premise sales, field and channel teams to define key performance indicators (KPIs) and keep metrics and reporting consistent across the channel.
Proactively challenge requests and assumptions where a different analytical approach would better answer the business question. Establish agreement where teams have different definitions, requirements or interpretations of performance.
Communicate complex analysis clearly to both technical and non-technical audiences.
Analyse large volumes of structured and unstructured data from various sources: internal and external market data.
Use SQL, Power BI and Excel to independently interrogate, combine and analyse complex commercial datasets.
Design and document appropriate quantitative methods for incomplete data, including sampling, estimation, extrapolation and sensitivity analysis.
Develop and maintain robust approaches to entity matching and de-duplication.
Use SQL and other programming tools (e.g., Python) to clean, transform, reconcile and prepare data for analysis, including messy outlet names, addresses and geospatial data, selecting the most efficient tool for the job.
Identify and resolve data quality issues affecting analysis and reporting.
Leverage tools such as Snowflake, Power BI, or other BI platforms to develop and maintain On Premise reporting and data visualisation needs.
Automate recurring reporting and manual data preparation so that the team spends its time interpreting numbers rather than assembling them.
Prepare On Premise data assets for AI-enabled use cases through clear definitions, documented lineage and structured context, so that AI tools return answers the business can trust.
Stay informed about emerging technologies and methods in automation, data analytics, and FMCG business processes.
Red Bull stands for individuality, authenticity and creativity. This is also what we expect from our employees. If you'd like to become part of Red Bull, bring your true and unique self to the application process.
Finding the right person for a role requires a thorough selection process. We may require a personality assessment, a video and/or in-person interview, an assignment or even a job simulation. The hiring team will share details of the process in advance.
Throughout your recruitment journey, you’ll come across moments where using AI could be an option. We encourage you to approach this with the same freedom & responsibility we offer our employees. Our recruitment process is all about getting to know you as an individual - what makes you unique, your strengths, your passions. You might use AI to polish your resume or prepare for interviews but remember nothing beats real human connection. When it comes to Red Bull Wingfinder or a video assessment, we want to see and hear your personality and feel the energy you bring. Likewise, think of a Case Study as more than just a task. It’s your chance to show us what you can really do, experience the role, and assess if it’s the right fit for you. By relying on AI, you risk missing the chance to truly stand out!
Once you submit your application, you will receive an acknowledgement email. Afterwards you can expect to hear from us within two weeks.
During the interview process you will have the chance to gauge your talents and show your drive and motivation. The hiring team will ask you about your experiences, skills and strengths that are most relevant to the job in order to get a good picture of your profile and your unique selling points.