Lead Statistician / Lead Statistical Data Scientist

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 the Lead Statistical Data Scientist, you'll provide technical leadership for the models, methods and analytical approaches that power Oritain's origin-verification science. You'll help set the direction of our data science capability while remaining close enough to the work to solve complex problems, guide projects and support delivery.

This is a role for someone who enjoys building as much as leading.

You’ll mentor and develop other data scientists, help shape how we approach technical challenges, and work across science, engineering, product and commercial teams to ensure our statistical solutions create real-world impact.

You’ll be joining a business in an exciting stage of growth. We're beyond the start-up phase, but we're still creating processes, improving ways of working and building capabilities. That creates a huge opportunity for someone who enjoys ownership, influence and helping bring clarity to complexity.

The people who thrive at Oritain are motivated by building, improving and creating. They enjoy helping others succeed and are open to feedback and learning, regardless of experience level. They bring energy, curiosity and a clear point of view. They can make progress when information is incomplete and know how to balance speed with quality.

Key Responsibilities

• Provide technical leadership across statistical and machine learning projects.
• Mentor and support other data scientists, helping raise capability across the team.
• Lead a high-performing, engaged team that delivers meaningful outcomes and contributes positively to Oritain's culture.
• Partner with stakeholders to understand problems, develop solutions and assess wider business impact.
• Build statistical models and machine learning approaches that turn data into decisions.
• Develop and deploy predictive models that solve business and operational challenges.
• Work with large and complex datasets from diverse sources.
• Create visualisations, dashboards and reporting tools that communicate insight clearly.
• Work cross-functionally to embed data science into products, workflows and decision-making processes.
• Keep up with developments in statistics and data science and bring the useful ones into our analytics.
• Provide trusted expert guidance to internal and external stakeholders.

Skills & Experience

We're looking for someone with deep statistical expertise, strong commercial awareness and a track record of helping others succeed.

Essential

• A minimum of 8 years of industry experience applying statistics, mathematics and machine learning to real-world problems.
• Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred).
• Deep understanding of probability, statistics, uncertainty, linear algebra and calculus.
• Extensive experience working with large datasets, data preparation and machine learning workflows.
• Proven experience applying classification, clustering, dimension reduction and other machine learning techniques.
• Strong programming capability and experience writing efficient, maintainable code in collaborative environments.
• Advanced Python and R expertise.
• Experience working with modern development tools and practices, including GitHub, VS Code, Conda and cloud environments.
• An ability to balance technical rigour with practical business outcomes.
• Strong communication skills and confidence working with stakeholders across different functions and levels.
• A passion for mentoring, coaching and growing technical talent.
• Sound judgement, curiosity and a willingness to challenge assumptions when better solutions exist.

Nice To Have

• Experience with Databricks or similar analytics platforms.
• Experience with HTML, JavaScript or related technologies.
• Previous experience in a scaling technology, analytics or science-led business.
• Experience leading teams through growth and change.

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.

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.

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