At a Glance
- Tasks: Design and deploy machine learning models to drive business decisions and optimise operations.
- Company: Join Travis Perkins plc, a leader in the trade distribution sector.
- Benefits: Enjoy competitive salary, bonuses, private medical insurance, and discounts across various businesses.
- Other info: Hybrid working model with excellent career growth opportunities.
- Why this job: Make a real impact with your data skills in a supportive, innovative environment.
- Qualifications: Bachelor's degree in a quantitative field and 2+ years of relevant experience required.
The predicted salary is between 63000 - 77000 £ per year.
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!
Contract Type: Permanent - Full time
Salary: Competitive + bonus + benefits
Location: Northampton, Northamptonshire
hrs/pw: Monday - Friday / Hybrid 1-2 days per week office based
Reference: 75368
Data Scientist in Northampton employer: Travis Perkins
At Travis Perkins plc, we pride ourselves on being an exceptional employer that values operational excellence, diversity, and talent development. As a Regional Director in the Central Midlands, you'll have the opportunity to lead a dynamic team, drive meaningful change, and foster a culture of inclusion while enjoying competitive benefits and a supportive work environment. Join us to make a significant impact in a key leadership role and help shape the future of our region.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Northampton
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Scientist in Northampton
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Travis Perkins, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Travis Perkins. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Travis Perkins
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Travis Perkins!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
