Statistical Data Scientist

Statistical Data Scientist Build models that matter. Join Oritain and apply cutting-edge statistics and machine learning to help global brands prove where their products come from, reducing fraud and driving trust. Apply We usually respond within two weeks Oritain is a global leader in forensic origin verification of products and raw materials. With offices in Auckland, Dunedin, London, Paris, Singapore and Washington D.C, our vision is to be the source of truth in global supply chains. Through our proprietary methodology, our mission is to harness cutting edge science, data, and specialized services to create a community of origin verified buyers and suppliers, protecting our people and planet. We empower the world’s leading brands to make positive changes across their supply chain; ensuring product integrity, meeting regulatory demands, and reducing the risk of fraud and unethical sourcing - creating real change in our world. About the Role As a Statistical Data Scientist, you'll build the statistical models and machine learning methods behind our origin-verification science, then work with teams across Oritain to get those models running within live products and workflows. You'll partner with scientists, engineers, product teams and business stakeholders to turn complex data into solutions that solve real customer problems. From developing predictive models to improving analytical approaches and supporting decision-making, your work will have a direct impact on our products, customers and future growth. This role sits in a business that is growing fast. We're building, evolving and scaling. That means you'll have the opportunity to shape how things are done, influence decisions, and contribute well beyond the boundaries of a traditional data science role. If you're looking for an environment where ownership is encouraged, ideas are welcomed, and your work can genuinely move the business forward, Oritain is the right place for you. Key Responsibilities Collect, clean and process data from a range of sources. Build statistical models and machine learning algorithms that turn data into decisions. Develop and deploy predictive models to solve operational and commercial challenges. Build visualisations, dashboards and analytical tools that make insight easy to use. Work closely with cross-functional teams to embed analytical solutions into existing products and workflows. Evaluate and improve modelling approaches using rigorous quantitative assessment. Track developments in statistics and data science and bring the useful ones into our analytics. Provide expert guidance on data science initiatives across the organisation. Skills & Experience A degree in Statistics, Mathematics, Machine Learning, Data Science or a related field (postgraduate study preferred). A minimum of 2 years of commercial experience applying statistical modelling and machine learning techniques to real-world problems. Solid grounding in probability, statistics, uncertainty, linear algebra and calculus. Experience working with large datasets, data transformation and cleaning. Experience with classification, clustering, dimension reduction and other machine learning methods. Experience using software development tools such as VS Code, Conda and GitHub, and working with command line tools and Unix-based operating systems, including environment management. Experience using Python and R to develop and deploy models in cloud environments (Azure experience is advantageous). Understanding of machine learning lifecycles and MLOps principles. Experience working with databases, APIs and collaborative development tools. Sharp problem-solving and analytical skills, with attention to detail and sound judgement. Confident communication skills, including the ability to explain technical concepts to non-technical audiences. An open, curious and learning-oriented approach, with a commitment to doing great work. Nice to have: Experience with Databricks or similar platforms. Experience with HTML, JavaScript or related technologies. Exposure to supply chain, sustainability or risk-focused analytics environments. Company Benefits Hybrid working (minimum 3 days per week in our Farringdon office) 35 days paid leave, inclusive of public holidays Birthday off Enhanced Maternity and Paternity Leave Life insurance Healthcare Cash Plan Employee Assistance Programme (EAP) Pension Monthly Wellbeing Allowance Breakfast, snacks, Friday lunch and barista coffee in the office Learning portal with over 100,000 assets for professional development We believe great teams are built from different perspectives, experiences, and ways of thinking. We welcome applications from everyone and encourage you to bring your whole self to the process. If there’s anything we can do to support you, including any reasonable adjustments at any stage of hiring, please let the team know. Department Data Science and Analytics Locations London Remote status Hybrid Employment type Full-time About Oritain Oritain is a global leader in forensic origin verification. Using cutting edge science, advanced technology, and specialized services, we independently verify where products and raw materials come from – protecting brand integrity, supporting compliance, and strengthening supply chain trust and transparency. Our method is highly resistant to tampering, court-admissible, and trusted by suppliers and manufacturers, brands and retailers, consumers, and regulators. Driven by purpose, we are committed to advancing the scientific techniques and systems needed to identify the origin of the world’s most critical commodities – enabling more ethical, resilient, and accountable supply chains.