At a Glance
- Tasks: Transform data into powerful insights for a growing eCommerce business.
- Company: Join a dynamic team at Lands' End, based in Oakham, Rutland.
- Benefits: Enjoy hybrid working, gym access, employee discounts, and more!
- Other info: Collaborative environment with opportunities for personal and professional growth.
- Why this job: Make a real impact by optimising marketing and driving business decisions.
- Qualifications: Experience in Data Science and strong analytical skills required.
The predicted salary is between 45000 - 55000 £ per year.
Location: Oakham, Rutland, United Kingdom
Love Data and want to support a growing eCommerce business to turn data into powerful business outcomes? We are looking for a Data Scientist for our European Analytics Team. The Data Scientist is a new role in our growing Europe Analytics Team, which sits within a wider European team based in Oakham, Rutland and Mettlach, Germany. The role will be supporting multiple markets (UK, Germany, France, Austria) and will help build and shape the data science capability and strategy for Lands’ End in Europe.
This is a hands-on, high-impact role where you will apply advanced analytics and data science techniques to unlock deeper customer understanding, optimise marketing performance, and drive commercial decision making across the business. You will work across Marketing, Merchandising, E-commerce and Operations to enable intelligent decision making at all levels. This role combines deep technical expertise with strong commercial application, helping translate complex data into actionable business outcomes.
Our team operates a hybrid working model with a minimum of 9 days on site each month; however, remote options will be considered for the right candidate.
What you can expect from the Role:
- Advanced Analytics and Modelling
- Apply segmentation and clustering techniques to refine customer targeting
- Build attribution and measurement frameworks for marketing activity
- Support pricing and promotional optimisation through quantitative analysis
- Data Product Development
- Design and build reusable data science products and pipelines
- Support automation of reporting and decision-making tools
- Work with engineering and IT teams to scale solutions within our analytics ecosystem
- Insight & Business Impact
- Translate complex outputs into clear, compelling recommendations
- Partner with stakeholders across Marketing, Trading and Digital teams
- Drive measurable improvements in customer engagement, revenue and profitability
- Collaboration & Capability Building
- Act as a technical expert within the analytics team, supporting analysts and stakeholders
- Promote best practice in statistical methods, experimentation and modelling
- Contribute to building a data-driven culture across the business
What we expect from you:
- Proven experience in Data Science, Advanced Analytics or similar role
- Experience applying data science in a commercial setting (e.g. retail, eCommerce, marketing)
- Proven ability to deliver measurable business impact from data
- SQL and experience working with large, complex datasets
- Solid understanding of:
- Statistical modelling
- Machine learning techniques
- Experimental design and testing
- Experience with cloud/data platforms or scalable pipelines
- Strong problem-solving and analytical thinking
- Ability to structure ambiguous problems into clear analytical approaches
- Experience linking analysis to business outcomes (not just modelling)
Personal Skills:
- Excellent communication skills – able to explain complex concepts clearly
- Strong stakeholder management across multiple functions
- Comfortable working cross-functionally
- Enthusiastic and creative, always looking for innovative solutions to business problems
- Personal pride, ensuring that work is always delivered to high standard
- Tenacious and driven to improve yourself, and the way things are done
- The ability to multi-task, especially when under pressure, and effectively prioritise
- The ability to work in a fast paced, changing environment
Benefits you will receive:
- Hybrid Working Model
- Subsidised Restaurant
- Free access to a local Gym & Swimming Pool
- 50% Employee Discount
- Cash Health Scheme
- Free Annual Eye test
- Employer pension contribution up to 5%
- Free on-site parking
Data Scientist in Oakham employer: Lands' End, Inc
At Lands' End, we pride ourselves on being an exceptional employer, offering a dynamic work environment in Oakham, Rutland, where innovation meets collaboration. Our hybrid working model promotes flexibility, while our commitment to employee growth is evident through opportunities for skill development and cross-functional teamwork. With benefits like a subsidised restaurant, gym access, and a generous employee discount, we ensure that our team members feel valued and supported as they contribute to meaningful business outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Oakham
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even local events. The more you engage with others, the better your chances of landing that Data Scientist role.
✨Show Off Your Skills
Don’t just talk about your experience; showcase it! Create a portfolio of projects that highlight your data science skills. This could be anything from personal projects to contributions to open-source. Let your work speak for itself!
✨Ace the Interview
Prepare for those interviews by practising common data science questions and case studies. Be ready to explain your thought process and how you’ve used data to drive business outcomes. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist in Oakham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience in data science, advanced analytics, and any relevant commercial applications. We want to see how your skills can directly impact our eCommerce business!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how you can help us turn insights into powerful business outcomes. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise! Mention your experience with SQL, statistical modelling, and machine learning techniques. We’re looking for someone who can translate complex data into actionable insights, so make it clear how you’ve done this in the past.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Lands' End, Inc
✨Know Your Data Science Stuff
Make sure you brush up on your data science techniques, especially those mentioned in the job description like statistical modelling and machine learning. Be ready to discuss how you've applied these skills in a commercial setting, as this will show your practical experience.
✨Prepare for Real-World Scenarios
Think about specific examples where your data analysis led to measurable business outcomes. Prepare to explain how you approached ambiguous problems and what impact your solutions had on customer engagement or revenue. This will demonstrate your ability to link analysis to real business results.
✨Show Off Your Communication Skills
Since you'll be working cross-functionally, practice explaining complex data concepts in simple terms. You might be asked to present your findings or recommendations, so being able to communicate clearly and effectively is key. Think of ways to make your insights compelling and relatable.
✨Be Ready to Collaborate
Expect questions about teamwork and collaboration, as this role involves working with various stakeholders. Share examples of how you've supported others in your previous roles and promoted best practices in analytics. Highlight your enthusiasm for building a data-driven culture within a team.
