Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Statistical Data Scientist role.
Rezi rewrites your resume against Oritain's job description. Free.
Tailor your resume to this Statistical Data Scientist role.
Rezi rewrites your resume against Oritain's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Statistical Data Scientist posting at Oritain — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Statistical Data Scientist posting at Oritain — free, in seconds.
About the Role
As a Statistical Data Scientist, you will build the statistical models and machine learning methods behind Oritain's origin-verification science and deploy these models within live products and workflows. You will partner with scientists, engineers, product teams, and business stakeholders to transform complex data into solutions for customer problems, impacting products, customers, and future growth. This role offers the opportunity to shape processes, influence decisions, and contribute beyond a traditional data science scope in a fast-growing business.
Responsibilities
- Collect, clean, and process data from various sources.
- Build statistical models and machine learning algorithms to derive decisions from data.
- Develop and deploy predictive models to address operational and commercial challenges.
- Create visualizations, dashboards, and analytical tools for easy insight utilization.
- Collaborate with cross-functional teams to integrate analytical solutions into products and workflows.
- Evaluate and enhance modeling approaches through rigorous quantitative assessment.
- Stay updated on statistics and data science advancements, applying useful ones to analytics.
- Provide expert guidance on data science initiatives across the organization.
Requirements
- A degree in Statistics, Mathematics, Machine Learning, Data Science, or a related field (postgraduate study preferred).
- Minimum of 2 years of commercial experience applying statistical modeling and machine learning techniques to real-world problems.
- Solid understanding of probability, statistics, uncertainty, linear algebra, and calculus.
- Experience working with large datasets, including data transformation and cleaning.
- Experience with classification, clustering, dimension reduction, and other machine learning methods.
- Proficiency with software development tools like VS Code, Conda, and GitHub.
- Experience 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.
- Understanding of machine learning lifecycles and MLOps principles.
- Experience with databases, APIs, and collaborative development tools.
- Sharp problem-solving and analytical skills with attention to detail and sound judgment.
- Confident communication skills, including explaining technical concepts to non-technical audiences.
- An open, curious, and learning-oriented approach with a commitment to high-quality work.
- Experience working with geospatial data / spatial statistics (nice to have).
- Experience with Databricks or similar platforms (nice to have).
- Experience with HTML, JavaScript, or related technologies (nice to have).
- Exposure to supply chain, sustainability, or risk-focused analytics environments (nice to have).
Skills
- Statistical modeling
- Machine learning
- Data processing
- Predictive modeling
- Data visualization
- Dashboard creation
- Analytical tool development
- Quantitative assessment
- Python
- R
- Cloud environments (Azure advantageous)
- MLOps
- Database management
- API integration
- Collaborative development
- Problem-solving
- Analytical skills
- Communication
- Geospatial data analysis
- Spatial statistics
- Databricks
- HTML
- JavaScript
Location
- London
Work Type
- Permanent
- Full Time
- Hybrid
Experience Level
- Minimum 2 years of commercial experience
Education Level
- Degree in Statistics, Mathematics, Machine Learning, Data Science, or related field
- Postgraduate study preferred
Benefits
- Hybrid working (minimum 3 days per week in 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
About the Company
- Oritain is a global leader in forensic origin verification of products and raw materials.
- Offices in Auckland, Dunedin, London, Paris, Singapore, and Washington D.C.
- Vision: To be the source of truth in global supply chains.
- Mission: Harness cutting-edge science, data, and specialized services to create a community of origin-verified buyers and suppliers, protecting people and the planet.
- Empowers 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.