{"id":3973053,"url":"https://alion.io/job/travis-perkins-data-scientist","title":"Data Scientist","company":{"id":2067308,"name":"Travis Perkins","domain":"travisperkinsplc.co.uk","url":"https://alion.io/company/travisperkinsplc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":{"grade":"A","score":100,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":8,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Hallucination","optional":false},{"name":"LightGBM","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NumPy","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"Travis CI","optional":false},{"name":"Vertex AI","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-11-09T16:55:16Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-11T10:36:35Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Travis Perkins plc is now hiring for an innovative, commercially minded Data Scientist to join our central Data Office within Group Technology.\nReporting 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.\nIf 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!\nWorking Pattern:\nHybrid Working:This role operates on a hybrid model, requiring attendance at our Northampton Head Office 1-2 days per week.\n\nThe Opportunity\nAs 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.\nWhat You'll Be Doing\nEnd-to-End Machine Learning:Designing, developing and deploying predictive and prescriptive models (e.g. demand forecasting, dynamic pricing, recommendation engines, and customer churn models).\n\nApplied AI & LLM Workflows:Developing modern AI capabilities, such as semantic search, retrieval-augmented generation (RAG) and generative AI workflows to augment business decision making.\n\nStakeholder Translation:Collaborating with colleagues across merchant branches, commercial and supply chain functions to translate operational challenges into actionable data science deliverables.\n\nProduction MLOps: Partnering with Data Engineering and Platform teams to transition prototype models into automated, scalable production pipelines using CI/CD, containerisation and cloud infrastructure.\n\nFeature Engineering & Data Assets: Designing resilient, reusable feature stores and data assets from raw enterprise data, ensuring high data integrity, reliability, and reproducibility.\n\nData Storytelling & Visualisation: Synthesising complex technical outputs into intuitive visualisations, dashboards, and clear narratives for executive and operational leaders to drive adoption.\n\nGovernance & AI Ethics:Ensuring all deployed models comply with data governance standards, GDPR, and AI ethical frameworks (including bias mitigation, transparency, and hallucination safeguards).\n\nAbout You\nEssential\nBachelor's degree in a quantitative discipline (Computer Science, Data Science, Statistics, Mathematics, Physics, or a related STEM field).\n\n2+ years of hands-on experience developing and deploying machine learning or statistical models within a commercial environment.\n\nAdvanced proficiency in Python (pandas, NumPy, scikit-learn) and advanced SQL.\n\nSolid understanding of core ML algorithms (e.g. XGBoost, LightGBM, linear/logistic regression, clustering, time-series forecasting).\n\nPractical familiarity with software engineering best practice, including Git, code reviews and reproducible workflows.\n\nAwareness of modern applied AI concepts (embeddings, vector search, prompt engineering, and open-source models).\n\nCommercial mindset with the ability to connect technical metrics (RMSE, AUC, latency) to tangible business outcomes (margin, conversion, stock holding).\n\nExcellent communication skills, with confidence explaining technical concepts clearly to non-technical stakeholders.\n\nWe'd Particularly Like to See\nMaster’s degree or higher in Data Science, Machine Learning, or Advanced Analytics.\n\nPractical experience within the Google Cloud Platform ecosystem (Vertex AI, BigQuery, BigQuery ML, Cloud Run).\n\nExperience working with MLOps frameworks, CI/CD pipelines, MLflow, and model drift monitoring.\n\nBackground in retail merchanting, trade distribution, supply chain logistics or e-commerce.\n\nExperience fine-tuning or integrating LLMs and generative AI frameworks in production.\n\nGoogle Cloud certifications.\n\nWhat's in it for you!\nCompany/ Performance related bonus\n\nSave-as-you-earn & Buy-as-you-earn schemes\n\nContributory pension scheme\n\nLife Insurance\n\nPrivate Medical Insurance\n\nColleague discount across a variety of Group businesses including with special discounts across our Trade Merchants - 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