Data Scientist / Analyst (Hybrid)

at  Imperial Brands

SKILLS AND EXPERIENCE REQUIRED

• Relevant experience in data science or analytics. Preferably in FMCG.
• Proficiency in Python, R, SQL, and experience with large consumer datasets.
• Fluency in English.
• Strong analytical and critical thinking skills.
• Commitment to data accuracy and quality.
• Willingness to travel 30% - 50% of the time across Europe.

ABOUT US

We’re a truly international company, fourth largest in our industry and operating across 120 markets. An inclusive, innovative global FMCG business supported by 25,000 employees. As we embrace a new era of growth, we are transforming. Our ways of working and culture are driven by a challenger mindset, constantly questioning the status quo where people can bring their best selves to work. Our agility and collaboration are driving our ambitions, innovation and success all supported by our award-winning development programmes that creates exciting and rewarding career opportunities for all. Encouraging inclusion at local levels and supporting a developing and robust diversity agenda globally, we’re fully committed to creating and maintaining an environment that celebrates and respects difference

THE ROLE

If you have a passion for data and a knack for uncovering valuable insights join us here at Imperial Brands as our Data Scientist / Analyst for Consumer Insights.
This is a great opportunity for the right person to develop their career and make a significant impact on our consumer experience and be part of an inclusive, innovative global FMCG business supported by 25,000 employees.
We want to hear from you!
Location: This role can be based in Amsterdam, Bristol (UK) or London (UK).

PRINCIPAL ACCOUNTABILITIES

• Analyze Large Datasets: Extract insights into consumer behavior, segmentation, and journeys.
• Advanced Analytics: Identify patterns and correlations to inform business strategies.
• Predictive Modeling: Develop models to support personalized communicationstrategies.
• Project Management: Handle multiple data science projects, ensuring timely delivery.
• Data Storytelling: Communicate complex concepts to non-technical stakeholders.