At a Glance
- Tasks: Design and build customer-focused Data Science use cases and deploy machine learning models.
- Company: Large retail organisation transforming its Data and AI capabilities.
- Benefits: Competitive salary, hybrid working, and opportunities for career growth.
- Other info: High visibility work with a focus on practical solutions and scalability.
- 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.
BI Data Modeler employer: Harnham
Join a large retail organisation at the forefront of its Data and AI transformation, where you will have the opportunity to make a tangible impact on customer-focused projects. With a collaborative and inclusive culture, this role offers hybrid working arrangements and the chance to grow alongside a dedicated Data Science team, ensuring your contributions are recognised and valued. Benefit from clear pathways for professional development as you help shape the future of data-driven decision-making within the company.
StudySmarter Expert Advice🤫
We think this is how you could land BI Data Modeler
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio of your Data Science projects, especially those that demonstrate your ability to take models into production. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common Data Science questions and case studies. Be ready to discuss how you've tackled real business problems using Python and SQL, and how you’ve deployed models effectively.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace BI Data Modeler
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 end-to-end Data Science projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for Data Science and how you can contribute to our journey. Mention specific projects or experiences that demonstrate your ability to drive measurable impact.
Showcase Your Projects:If you've got any relevant projects, especially those involving machine learning or model deployment, make sure to include them. We love seeing practical examples of your work and how you've tackled real business problems.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications 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 Fundamentals
Brush up on your core Data Science concepts, especially around machine learning and statistical modelling. Be ready to discuss how you've applied these in real-world scenarios, particularly in a commercial context.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python and SQL. You might be asked to solve a problem on the spot, so practice coding challenges that involve data manipulation and model deployment.
✨Understand the Business Impact
Familiarise yourself with how Data Science can drive value in a retail environment. Think of examples where your work has led to measurable outcomes, and be ready to share these during the interview.
✨Engage with Stakeholders
Since the role involves working closely with commercial teams, prepare to discuss how you would translate business problems into practical modelling solutions. Highlight any past experiences where you've successfully collaborated with non-technical stakeholders.
