Technology at Primark
Our technology team is actively shaping the next wave of advancements. Engaged with innovative initiatives, your expertise will propel our business into the future. Collaborating with a creative team of tech enthusiasts, you’ll contribute your unique skills to fuel our technological advancements.
We are seeking a Data Scientist to join Primark’s Data Science & Measurement team, delivering advanced analytics, experimentation and data science solutions that drive better business decisions. You will work closely with Data Scientists, Data Engineers, Analytics teams and business stakeholders to solve complex challenges using data. Leveraging Python, SQL, statistics and machine learning, you will develop models, analyse large datasets and generate actionable insights. This is a hands-on role for a commercially minded professional who can translate complex analysis into clear recommendations. You will contribute to reusable analytical assets, robust methodologies and scalable solutions that support business growth. The role offers an exciting opportunity to help shape Primark’s growing data science capability and deliver measurable business value.
Job DescriptionWhat you'll do
Data Science & Advanced Analytics: Design and deliver data science solutions including predictive modelling, forecasting, segmentation, optimisation, experimentation and measurement to support better business decisions and measurable outcomes.
Data Preparation & Analysis: Build, transform and analyse complex datasets using Python, SQL, Databricks and modern analytics tools to create robust analytical datasets and scalable workflows.
Machine Learning & Statistical Modelling: Develop, evaluate and monitor machine learning and statistical models, applying best practices across feature engineering, model validation, documentation and performance assessment.
Experimentation & Commercial Insight: Support A/B testing and measurement initiatives, helping to define hypotheses, assess results and quantify the commercial impact of business decisions and interventions.
Stakeholder Partnership & Storytelling: Work closely with business stakeholders and senior data professionals to translate complex analytical findings into clear, compelling recommendations that drive action.
Cross-Functional Collaboration: Partner with Data Engineers, Analytics teams and platform specialists to productionise analytical solutions, improve scalability and ensure operational reliability.
Continuous Improvement & Data Science Innovation: Contribute to reusable analytical assets, coding standards and best practices while identifying opportunities to automate processes, improve analytical quality and increase adoption of data science solutions across the business.
What you'll bring
Data Science Experience (2-5 Years): Experience applying data science, machine learning, statistical modelling and advanced analytics techniques to solve real-world business problems and deliver measurable outcomes.
Python, SQL & Analytical Expertise: Strong Python and SQL skills, with experience building robust, reproducible analyses and working with large datasets in modern analytics environments such as Databricks, Spark or cloud-based platforms.
Machine Learning & Statistical Foundations: Solid understanding of supervised and unsupervised learning, feature engineering, model evaluation, experimentation, A/B testing and statistical analysis techniques.
Business Problem Solving & Commercial Mindset: Ability to translate business questions into analytical approaches, testable hypotheses and practical solutions that support commercial decision-making and value creation.
Data Storytelling & Stakeholder Engagement: Proven ability to communicate complex analytical findings through clear narratives, visualisations and recommendations that influence technical and non-technical stakeholders.
Collaboration & Delivery: Experience working effectively across Data Science, Analytics, Engineering and business teams, balancing analytical rigour with pragmatic delivery in fast-paced environments.
Continuous Learning & Innovation: Demonstrated curiosity for emerging technologies, data science techniques and AI capabilities, with a commitment to quality, simplicity and continuous improvement.
About Primark
At Primark, people matter. They’re the beating heart of our business and the reason we’ve grown from our first store in Dublin in 1969 to a £9bn+ turnover business and over 80,000 colleagues and over 440 stores in 17 countries today. Our values run through everything we do. In essence, we're Caring and always strive to put people first. We're also Dynamic, bravely pushing the boundaries to stay ahead. And finally, we succeed Together.
If you need any reasonable adjustments or have an accessibility request, during your recruitment journey, such as extended time or breaks between online assessments, a sign language interpreter, mobility access, or assistive technology please contact your talent acquisition specialist.
All offers of employment are subject to background checks, including right to work, reference education and for some roles criminal, and financial checks. If you have any concerns, please reach out to our talent acquisition team to discuss.
Skills Required
- 2-5 years data science experience applying ML and statistical modelling to business problems
- Strong Python programming skills
- Strong SQL skills and experience working with large datasets
- Experience with Databricks, Spark or other cloud-based analytics platforms
- Practical machine learning knowledge (supervised/unsupervised learning, feature engineering, model validation, monitoring)
- Experimentation and A/B testing experience, including hypothesis design and result assessment
- Ability to translate analytical findings into clear business insights and visualisations for stakeholders
- Experience collaborating with Data Engineers, Analytics and platform teams to productionise solutions
Primark Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Primark and has not been reviewed or approved by Primark.
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Fair & Transparent Compensation — Pay is often characterized as fair or good compared to similar retail roles, and overtime availability can improve take-home earnings. Recent UK minimum-rate increases and the removal of age-related pay tiers reinforce a sense of improving pay fairness.
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Leave & Time Off Breadth — Paid time off stands out as comparatively strong for retail, with full-time roles described as having notably generous PTO alongside sick time and paid holidays. This breadth can increase the overall value of the compensation package beyond hourly wages.
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Parental & Family Support — Enhanced maternity, paternity, adoption, and surrogacy payments are positioned as meaningful additions to the rewards package. Ongoing colleague discounts and family-oriented support contribute to a more rounded benefits offering.
Primark Insights
What We Do
Primark is an international fashion retailer employing more than 80,000 colleagues across 17 countries in Europe and the US. Founded in Ireland in 1969 under the Penneys brand, Primark aims to provide affordable choices for everyone, from great quality everyday essentials to stand-out style across women’s, men’s and kids, as well as beauty, homeware and accessories. With a focus on creating great retail experiences, Primark has over 440 stores globally and continues to expand with the aim of reaching 530 stores by the end of 2026. Primark is working to make more sustainable fashion affordable for everyone through its Primark Cares strategy, a multi-year programme that focuses on giving clothing a longer life, protecting life on the planet and supporting the livelihoods of the people who make Primark clothes. As part of this, Primark unveiled nine commitments it is working to achieve by 2030. These commitments include making all of its clothes from recycled or more sustainably sourced materials by 2030, halving carbon emissions across its value chain and pursuing a living wage for workers in its supply chain.
