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Travis Perkins

UK building materials wholesaler and retailer

Data Scientist

Applied Machine LearningPosted on Nov 9
Full-timeNorthampton, UK

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Physics, or a related STEM field is required.
  • At least 2 years of hands-on experience developing and deploying machine learning or statistical models in a commercial environment is required.
  • Advanced proficiency in Python, including pandas, NumPy, and scikit-learn, and advanced SQL are required.
  • A solid understanding of core machine learning algorithms, including XGBoost, LightGBM, linear and logistic regression, clustering, and time-series forecasting, is required.
  • Practical familiarity with software engineering best practices, including Git, code reviews, and reproducible workflows, is required.
  • Awareness of applied AI concepts, including embeddings, vector search, prompt engineering, and open-source models, is required.
  • The candidate must connect technical metrics such as RMSE, AUC, and latency to business outcomes such as margin, conversion, and stock holding.
  • The candidate must explain technical concepts clearly to non-technical stakeholders.

Responsibilities

  • Design, build, and deploy production-ready machine learning models and practical AI solutions.
  • Own the full model lifecycle, from exploratory analysis and feature engineering through proof-of-concept prototyping and production pipeline deployment.
  • Design, develop, and deploy predictive and prescriptive models, including demand forecasting, dynamic pricing, recommendation engines, and customer churn models.
  • Develop applied AI capabilities, including semantic search, retrieval-augmented generation, and generative AI workflows to support business decision-making.
  • Collaborate with colleagues across merchant branches, commercial functions, and supply chain functions to translate operational challenges into actionable data science deliverables.
  • Partner with Data Engineering and Platform teams to transition prototype models into automated, scalable production pipelines using CI/CD, containerisation, and cloud infrastructure.
  • Design resilient, reusable feature stores and data assets from raw enterprise data while ensuring data integrity, reliability, and reproducibility.
  • Translate technical outputs into visualisations, dashboards, and clear narratives for executive and operational leaders to support adoption.
  • Ensure deployed models comply with data governance standards, GDPR, and AI ethical frameworks, including bias mitigation, transparency, and hallucination safeguards.

Desired Qualifications

  • A master's degree or higher in Data Science, Machine Learning, or Advanced Analytics is preferred.
  • Practical experience with Google Cloud Platform tools, including Vertex AI, BigQuery, BigQuery ML, and Cloud Run, is preferred.
  • Experience with MLOps frameworks, CI/CD pipelines, MLflow, and model drift monitoring is preferred.
  • A background in retail merchanting, trade distribution, supply chain logistics, or e-commerce is preferred.
  • Experience fine-tuning or integrating large language models and generative AI frameworks in production is preferred.
  • Google Cloud certifications are preferred.

About the Company

Travis Perkins

UK building materials wholesaler and retailer

Travis Perkins is a large UK supplier of building materials and home improvement products. It grew from two family businesses (Perkins & Co and Travis timber importers) that merged in 1988 and expanded through acquiring many other businesses, including Wickes in 2005, to serve both tradespeople and DIY customers. Its operations center on distributing a wide range of products—timber, bricks, plaster, plumbing and heating, decorating, tools, and related building supplies—through a network of branches and direct-to-consumer channels, plus online ordering. The company differentiates itself by its scale, diversified portfolio of brands and outlets, and a strong emphasis on growth through acquisitions that widen its geographic reach and product offerings. Its goal is to remain a leading UK building materials and home improvement group by expanding its reach, product range, and service capabilities across both trade and consumer markets.

Company size
10,001+
Company stage
IPO
Headquarters
Northampton, United Kingdom
Founded
1960

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