At a Glance
- Tasks: Develop data products and analytics solutions to drive business performance and sustainability.
- Company: Join Danone, a leader in health-focused nutrition with a commitment to sustainability.
- Benefits: Competitive salary, bonus, flexible benefits, and opportunities for continuous learning.
- Other info: Collaborative culture that values diversity and inclusion.
- Why this job: Shape the future of data-driven decision-making in a dynamic and impactful environment.
- Qualifications: Experience in data visualisation, SQL, Python, and cloud platforms required.
The predicted salary is between 35000 - 45000 £ per year.
Danone’s mission—“Bringing health through food to as many people as possible”—is at the heart of everything we do. In the UK&I, we are leveraging data to drive profitable, sustainable growth and support our One Planet. One Health vision. Our recent investments in cloud data platforms, analytics, and digital transformation are enabling us to deliver actionable insights, improve productivity, and accelerate our sustainability agenda. The Data & Analytics function is a greenfield opportunity, offering the chance to shape how data drives business decisions at Danone UK&I.
Role Purpose
The Data Analyst will:
- Develop and deliver data products that enable business performance management and strategic decision‑making.
- Mine, extract, and transform data from Danone’s cloud datalake and other enterprise systems.
- Build analytics solutions and visualisations that support commercial, operational, and sustainability objectives.
- Support the Director of Data & Analytics in developing proof‑of‑concept (PoC) projects, especially those that demonstrate the value of data in digital, commercial, and financial domains.
Key Accountabilities & Deliverables
- Design, monitor, and manage performance and data quality KPIs across multiple functions.
- Develop and maintain dashboards and reports using Power BI, Snowflake, and Databricks.
- Extract, clean, and transform data using SQL and Python, ensuring data integrity and traceability.
- Collaborate with business stakeholders to translate commercial and operational challenges into analytical questions and actionable insights.
- Document data provenance, sources, and recommended usage to support data governance and compliance.
- Contribute to Danone’s sustainability and digital transformation initiatives by embedding relevant data and analytics into business processes.
Stakeholder Engagement
- Partner with commercial, operations, finance, and master data teams at both UK&I and global levels.
- Build analytical capability by delivering data products, dashboards, ad‑hoc analyses, and PoC projects.
- Influence and support business teams in adopting data‑driven decision‑making.
Functional Expertise
- Advanced skills in data visualisation (Power BI/Tableau) and experience building interactive dashboards for business users.
- Proficient in SQL and Python for data extraction, transformation, and analysis.
- Experience with cloud data platforms (Databricks, Snowflake) and data pipeline automation.
- Strong understanding of data governance, data quality management, and documentation best practices.
- Ability to translate business requirements into analytical solutions and communicate findings to non‑technical stakeholders.
Critical Expertise
- Demonstrated experience (2+ years) in developing data products that have delivered measurable business value (e.g., improved forecasting, reduced churn, enhanced commercial performance).
- Strong statistical and analytical reasoning, including experience with predictive modelling, clustering, and classification techniques.
- Proven ability to manage multiple priorities and deliver to tight deadlines in a matrix organisation.
- Experience supporting or leading PoC projects, ideally in FMCG or a similar fast‑paced environment.
- Stakeholder management and influencing skills, with the ability to work across functions and geographies.
About You
- Team player with strong collaboration and communication skills.
- Curious, committed, and enthusiastic about Danone’s mission and values.
- Highly numerate, analytical, and detail oriented.
- Confident in presenting data‑driven insights and recommendations to senior stakeholders.
- Proactive, adaptable, and comfortable with ambiguity in a rapidly evolving environment.
- Committed to continuous learning and development, with a growth mindset.
Please note that the salary on offer for this position is between £35,000 - £45,000 + bonus & benefits.
At Danone UK & Ireland, we are committed to delivering better health through better nutrition for millions of consumers and patients in our communities. We have a range of flexible benefits and excellent rewards. Diversity, Equity, and Inclusion (DEI) is deeply embedded in Danone’s DNA, representing our core values and beliefs. We embrace diversity as a driving force for positive change, nurturing an inclusive workplace where every individual is valued.
The closing date for applications is 06/01/26, you will therefore hear about your application after this date.
Data Analyst employer: Danone
Danone UK&I is an exceptional employer, dedicated to fostering a culture of collaboration and innovation while prioritising employee growth and development. With a strong commitment to sustainability and health, employees are empowered to leverage cutting-edge data technologies in a supportive environment that values diversity and inclusion. The opportunity to shape the future of data-driven decision-making within a global leader in nutrition makes Danone a truly rewarding place to work.
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We think this is how you could land Data Analyst
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Analyst
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!
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Craft a Tailored Cover Letter:For a full-time role at Danone, 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 Danone. 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 Danone
✨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!
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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 Danone!
✨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.
