Job Description
What you'll do
Advanced Analytics & Machine Learning Delivery: Lead the design, development and deployment of machine learning, optimisation and measurement solutions that solve complex business challenges and deliver measurable commercial value.
Data Science Product Development: Build and maintain scalable data science products, including predictive models, forecasting solutions, segmentation, recommendation engines and experimentation frameworks that support business decision-making.
Data Engineering & Model Productionisation: Develop robust analytical datasets and machine learning pipelines using Databricks, Python, SQL and Spark, ensuring solutions are scalable, reliable and production-ready.
Stakeholder Partnership & Commercial Impact: Partner with business stakeholders to define hypotheses, success measures and value metrics, translating analytical insights into actionable recommendations that improve commercial outcomes.
Experimentation & Measurement Leadership: Lead experimentation, testing and measurement initiatives, using statistical methods and causal inference techniques to evaluate business performance and impact.
Technical Leadership & Team Development: Mentor Data Scientists and Analysts, sharing best practices across modelling, experimentation, coding standards and commercial problem solving.
Data Science Strategy & Innovation: Contribute to the data science roadmap, champion best practices and develop innovative retail-focused solutions across areas such as pricing, forecasting, customer behaviour and operational efficiency.
What you'll bring
Advanced Data Science Experience (5-8 Years): Strong hands-on experience delivering machine learning, statistical modelling, optimisation and advanced analytics solutions within commercial environments.
Python, SQL & Data Platform Expertise: Advanced Python and SQL skills, with experience building reproducible machine learning workflows using Databricks, Spark or similar large-scale data processing technologies.
Machine Learning & Statistical Expertise: Deep understanding of supervised and unsupervised machine learning, feature engineering, model evaluation, experimentation and performance monitoring techniques.
Retail & Commercial Analytics: Experience applying data science in retail, consumer, grocery, apparel or other high-volume environments, delivering solutions that support business performance and decision-making.
Experimentation & Value Measurement: Experience designing, executing and interpreting experiments, measurement frameworks and analytical initiatives that deliver measurable business value.
Stakeholder Engagement & Communication: Ability to translate business challenges into analytical solutions and communicate complex findings through clear, compelling recommendations.
Leadership & Continuous Improvement: Experience mentoring colleagues, driving best practices and contributing to the growth, innovation and maturity of a high-performing Data Science function.
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.
