ESSENTIAL QUALIFICATIONS & EXPERIENCE

• Degree in Data Science, Statistics, Computer Science or equivalent practical experience.
• Demonstrated experience (minimum 3 - 4 years) designing and delivering analytics solutions in a business or scientific environment.
• Expertise in Power BI and dashboard design.
• Expertise in data modelling
• Proficient in Python, R, or similar tools for data analysis and transformation.
• Strong SQL skills and experience working with relational databases.
• Hands-on experience with cloud platforms (Azure preferred) and version control systems (e.g., Git).
• Proven ability to lead initiatives and influence cross-functional teams without direct authority.
• Strong communicator who can tailor insights to a variety of audiences.
• Highly organised with the ability to prioritise competing demands in a dynamic, fast-paced environment.
• Demonstrates a growth mindset, curiosity, and commitment to continuous learning.

RECRUITMENT FRAUD

Cyber criminals advertise fake job adverts with prestigious employers as a way of stealing information or even defrauding individuals out of money. In the most sophisticated cases, they will set up fake websites, which have a similar address to companies like Unilever. They even conduct fake telephone interviews and then offer candidates a role with the proviso they pay a fee for background checks or to cover work visa costs. These types of attacks are becoming more common as more people are looking for employment in the economic climate.

JOB PURPOSE

As a Computational Engineer within the Safety, Environmental & Regulatory Science (SERS) team at Unilever, you will take the lead in designing, developing, and delivering robust data analytics solutions that inform business decisions and scientific research. You will own and drive the development of dashboards, reporting tools, and AI-driven analytics frameworks that support cross-functional teams across safety, sustainability, and innovation.
You’ll act as a subject matter expert in analytics best practices, proactively engaging with business stakeholders, scientists, and digital tool developers to identify needs, design fit-for-purpose solutions, and ensure continuous improvement of data capabilities. This is a unique opportunity to shape how data empowers Unilever’s scientific and regulatory agenda.