Lead Statistical Data Scientist
Summary
Oritain, a forensic origin-verification company for global supply chains, is hiring a Lead Statistical Data Scientist in London to technically lead its statistical/ML models, mentor data scientists, and build and deploy predictive models. Core stack: Python, R, GitHub, VS Code, Conda and cloud environments.
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.
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.
- 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.
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.
- Experience working with geospatial data / spatial statistics.
- 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.
- 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