At a Glance
- Tasks: Design and build customer-focused Data Science use cases and deploy machine learning models.
- Company: Large retail organisation undergoing a significant data and AI transformation.
- Benefits: Competitive salary, hybrid working, and opportunities for career growth.
- Other info: High visibility work with a chance to shape the future of Data Science.
- Why this job: Join a collaborative team and make a real impact on customer outcomes.
- Qualifications: Experience in Python, SQL, and end-to-end Data Science processes.
The predicted salary is between 45000 - 48000 £ per year.
This is a strong opportunity for a commercially minded Data Scientist to join a business at a genuine inflection point in its Data and AI journey. You will play a key role in moving the organisation from ad-hoc analytics to a scalable, production-led Data Science capability, with clear backing from leadership and real-world use cases already live.
They are a large retail organisation undergoing a significant data and AI transformation. The culture is collaborative, inclusive and pragmatic, with a strong focus on delivering value at pace rather than over-engineering solutions. Getting models into production and driving measurable impact is a core priority.
You will work hands-on within a small but growing Data Science function, partnering closely with the Data Science Lead, another Data Scientist, and wider data and commercial teams.
- Designing and building customer-focused Data Science use cases such as segmentation, lifetime value modelling and demand forecasting.
- Developing, testing and deploying machine learning models end to end, from problem definition through to production.
- Contributing to the development of a new Data Science platform and helping shape best practice as the function matures.
- Working closely with Data Engineers and Analysts to ensure data quality, scalability and smooth model deployment.
- Engaging with commercial and customer stakeholders to translate business problems into practical modelling solutions.
To succeed in this role, you will bring a practical, business-led approach to Data Science:
- Strong commercial experience using Python for Data Science and machine learning.
- Solid SQL skills and confidence working with large, complex datasets.
- End-to-end Data Science experience, including taking models into production.
- Experience applying statistical modelling or machine learning to real business problems.
- Experience with model deployment tools such as Vertex AI or Azure ML.
Hybrid working, with three days per week on site in Knowsley. The chance to help build a Data Science capability from an early stage. High visibility work tied directly to customer and commercial outcomes. Clear opportunity to grow alongside the team as Data Science scales across the business.
If you are a hands-on Data Scientist looking to work on production-focused, customer-led use cases in a collaborative environment, apply now to find out more.
Data scientist (marketing) employer: Harnham
Join a large retail organisation in Merseyside that is at the forefront of a transformative Data and AI journey, where your contributions will directly impact customer outcomes. With a collaborative and inclusive culture, you will have the opportunity to work hands-on within a growing Data Science team, developing practical solutions that drive measurable results. Enjoy hybrid working arrangements and clear pathways for professional growth as you help shape the future of Data Science within the company.
StudySmarter Expert Advice🤫
We think this is how you could land Data scientist (marketing)
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. Getting to know the team can give you insider info and make your application stand out.
✨Tip Number 2
Show off your skills in real-time! Consider doing a live coding challenge or a data analysis project that you can present during interviews. It’s a great way to demonstrate your hands-on experience with Python and SQL.
✨Tip Number 3
Prepare for those tricky questions! Think about how you’ve tackled real business problems with data science. Be ready to discuss your end-to-end process, from problem definition to model deployment.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Data scientist (marketing)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your experience with Python, SQL, and any relevant machine learning projects. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this Data Scientist role. Share specific examples of how you've tackled real business problems using data science techniques. Show us your passion for making an impact!
Showcase Your Projects:If you've worked on any end-to-end data science projects, make sure to include them in your application. We love seeing practical applications of your skills, especially those that have driven measurable outcomes.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Harnham
✨Know Your Data Science Stuff
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've taken models into production, as this role is all about practical application. Think of examples that showcase your end-to-end Data Science experience.
✨Understand the Business Context
This company is looking for someone who can translate business problems into Data Science solutions. Do your homework on their current data and AI initiatives, and be prepared to discuss how your skills can help them move from ad-hoc analytics to a more scalable approach.
✨Showcase Collaboration Skills
Since you'll be working closely with other Data Scientists, Data Engineers, and commercial teams, highlight your experience in collaborative environments. Share examples of how you've successfully partnered with others to deliver impactful results.
✨Prepare Questions About Their Data Strategy
Come armed with thoughtful questions about their Data Science platform and future plans. This shows you're genuinely interested in their journey and gives you a chance to demonstrate your strategic thinking around data and AI transformation.
