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Location
Hybrid
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Nov 11, 2026. First seen by Alion on Nov 9, 2026. Travis Perkins scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Travis Perkins is a British distributor of building materials headquartered in Northampton, England, supplying timber, building materials, plumbing and heating products and tool hire to trade customers and the construction industry. Its roots go back to a timber business founded in 1797, and the current company was formed by the 1988 merger of Sandell Perkins and Travis & Arnold; it is listed on the London Stock Exchange. The group runs Travis Perkins branches, Toolstation and other businesses, and hires HGV drivers, counter sales assistants, sales negotiators, IT operators and business analysts.

Travis Perkins plc is now hiring for an innovative, commercially minded Data Scientist to join our central Data Office within Group Technology.

Reporting directly to the Data Science Lead, you will design, build and deploy production-ready machine learning models and practical AI solutions. Working closely with commercial and operational teams, you’ll turn complex data into intelligent decision-making tools directly influencing how we drive revenue, optimise margins and sharpen operational efficiency across our market-leading brands.

If you are a passionate data practitioner who thrives on turning complex operational challenges into scalable data science products, we would love to hear from you!

Working Pattern:

  • Hybrid Working:This role operates on a hybrid model, requiring attendance at our Northampton Head Office 1-2 days per week.

The Opportunity

As a Data Scientist at Travis Perkins plc, you will have ownership of the full model lifecycle, from exploratory analysis and feature engineering to prototyping proofs of concept (POCs) and deploying automated production pipelines.

What You'll Be Doing

  • End-to-End Machine Learning:Designing, developing and deploying predictive and prescriptive models (e.g. demand forecasting, dynamic pricing, recommendation engines, and customer churn models).

  • Applied AI & LLM Workflows:Developing modern AI capabilities, such as semantic search, retrieval-augmented generation (RAG) and generative AI workflows to augment business decision making.

  • Stakeholder Translation:Collaborating with colleagues across merchant branches, commercial and supply chain functions to translate operational challenges into actionable data science deliverables.

  • Production MLOps: Partnering with Data Engineering and Platform teams to transition prototype models into automated, scalable production pipelines using CI/CD, containerisation and cloud infrastructure.

  • Feature Engineering & Data Assets: Designing resilient, reusable feature stores and data assets from raw enterprise data, ensuring high data integrity, reliability, and reproducibility.

  • Data Storytelling & Visualisation: Synthesising complex technical outputs into intuitive visualisations, dashboards, and clear narratives for executive and operational leaders to drive adoption.

  • Governance & AI Ethics:Ensuring all deployed models comply with data governance standards, GDPR, and AI ethical frameworks (including bias mitigation, transparency, and hallucination safeguards).

About You

Essential

  • Bachelor's degree in a quantitative discipline (Computer Science, Data Science, Statistics, Mathematics, Physics, or a related STEM field).

  • 2+ years of hands-on experience developing and deploying machine learning or statistical models within a commercial environment.

  • Advanced proficiency in Python (pandas, NumPy, scikit-learn) and advanced SQL.

  • Solid understanding of core ML algorithms (e.g. XGBoost, LightGBM, linear/logistic regression, clustering, time-series forecasting).

  • Practical familiarity with software engineering best practice, including Git, code reviews and reproducible workflows.

  • Awareness of modern applied AI concepts (embeddings, vector search, prompt engineering, and open-source models).

  • Commercial mindset with the ability to connect technical metrics (RMSE, AUC, latency) to tangible business outcomes (margin, conversion, stock holding).

  • Excellent communication skills, with confidence explaining technical concepts clearly to non-technical stakeholders.

We'd Particularly Like to See

  • Master’s degree or higher in Data Science, Machine Learning, or Advanced Analytics.

  • Practical experience within the Google Cloud Platform ecosystem (Vertex AI, BigQuery, BigQuery ML, Cloud Run).

  • Experience working with MLOps frameworks, CI/CD pipelines, MLflow, and model drift monitoring.

  • Background in retail merchanting, trade distribution, supply chain logistics or e-commerce.

  • Experience fine-tuning or integrating LLMs and generative AI frameworks in production.

  • Google Cloud certifications.

What's in it for you!

  • Company/ Performance related bonus

  • Save-as-you-earn & Buy-as-you-earn schemes

  • Contributory pension scheme

  • Life Insurance

  • Private Medical Insurance

  • Colleague discount across a variety of Group businesses including with special discounts across our Trade Merchants - 20% off at Toolstation

Ready to Shape the Future of Data & AI with Us?

If you are an ambitious Data Scientist looking to build impactful machine learning solutions in a supportive, forward-thinking environment, submit your application today!

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