Lead Statistician

Oritain

Auckland

On-site

NZD 90,000 - 120,000

Full time

14 days+

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Benefits offered by this job

35 days paid leave
Volunteering leave allowance
Enhanced parental leave
Life insurance
Healthcare cash-back plan
Employee Assistance Programme (EAP)
Monthly wellbeing allowance
Learning portal with 100,000+ professional development resources

Job summary

Oritain is seeking a Lead Statistician in Auckland to provide technical leadership and develop analytics solutions that enhance products and support business strategies. The ideal candidate will have advanced training in statistics or a related field and over 8 years of experience in data analysis and machine learning.

This role involves mentoring team members, conducting statistical analysis, and deploying predictive models to solve complex business challenges. Oritain offers a strong benefits package including 35 days paid leave and professional development opportunities.

Qualifications

  • 8+ years of relevant hands-on experience.
  • Strong foundations in probability, statistics, and linear algebra.
  • Ability to apply statistical methods to real-world data.

Responsibilities

  • Lead a high performing team that delivers results.
  • Conduct statistical analysis and build machine learning models.
  • Create visualizations to communicate statistical insights.

Skills

Statistical analysis
Machine learning
Data visualization
Python programming
R programming

Education

PhD in Statistics, Mathematics, or a related field

Tools

VS Code
Conda
GitHub

Job description

Oritain is the global leader in product verification, with locations in Auckland, Dunedin, London, Singapore and Washington D.C. Our vision is to be the source of truth in global supply chains and our mission is to harness science, technology and services to create a community of origin verified buyers and suppliers, protecting our people and planet.

Sustainability isn’t just about tackling climate change; it represents a growing conscience around our actions and the impact they have on people, animals and the planet. The personal, professional and governmental move to sustainable practice is driven by a desire to change our impact on the world, but we can’t do this without knowing the certainty of our actions. Transparency is one way of holding ourselves accountable, but for it to be effective, it must be underpinned by proven traceability. Our scientific traceability does just that. Working with Mother Nature, we help brands across fashion, food, and pharmaceutical industries verify the origin and authenticity of their products and raw materials. With this verified truth, brands are empowered to make changes across their supply chain to operate more sustainably and pass those assurances onto their consumers.

About The Role

Based in Auckland, the Lead Statistician at Oritain plays a key role in providing technical leadership and mentoring across projects, developing analytics solutions to enhance existing products, enable new products and to support business decisions and strategies. Working closely with other teams within Oritain, the role holds responsibility for integrating statistical analysis and solutions into existing workflows and systems.

Key Responsibilities
  • Provide technical leadership and mentor other team members.
  • Lead a high performing, engaged team that consistently delivers results, grows capabilities and contributes to a strong, collaborative culture within and outside the team.
  • Understand requirements, formulate problems, develop solutions, and assess impact and implications.
  • Identify stakeholders, collaborators and end-users, and keep them in the development loop.
  • Collect, clean and process data from various sources.
  • Conduct statistical analysis and build statistical models or machine learning algorithms to derive actionable insights.
  • Develop and deploy predictive models and algorithms to solve business and operational challenges.
  • Create visualisations, including interactive maps and dashboards, as well as reports to communicate statistical insights effectively.
  • Stay up to date with the latest advancements in statistics and data science and apply them to enhance analytics solutions.
  • Work cross-functionally with teams to integrate statistical analysis and products into existing workflows and systems.
  • Provide expert guidance and support to internal and external stakeholders.
Skills & Experience

Advanced academic training in statistics, mathematics, machine learning, or a related quantitative field (preferably PhD level) with 8+ years of relevant hands‑on experience.

Statistics & Mathematics
  • Strong foundations in probability, statistics, linear algebra, and calculus.
  • Ability to apply probabilistic and statistical methods to real‑world data and develop mathematically robust solutions for operational systems.
Machine Learning
  • Experience working with large datasets, including data transformation, cleaning, and management.
  • Practical application of machine learning methods such as classification, clustering, and dimensionality reduction, with rigorous performance evaluation.
Computing
  • Strong programming skills with experience in collaborative development environments.
  • Proficiency in Python and R for development and deployment, including parallel and distributed computing.
  • Familiarity with tools such as VS Code, Conda, and GitHub; knowledge of HTML or JavaScript is desirable.
Professional Skills
  • Strong analytical, problem‑solving, and communication skills.
  • Ability to lead technical work, collaborate across teams, and communicate complex ideas to non‑technical stakeholders.
  • Adaptable and able to deliver high‑quality work in a fast‑paced commercial environment.
Company Benefits
  • 35 days paid leave (inclusive of public holidays) + your birthday off
  • Volunteering leave allowance
  • Enhanced parental leave
  • Life insurance
  • Healthcare cash‑back plan
  • Employee Assistance Programme (EAP)
  • Monthly wellbeing allowance
  • Learning portal with 100,000+ professional development resources
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