About Oritain:
Our vision is to be the source of truth in global supply chains. To achieve this, we work with some of the world's largest and most valuable brands to support their ESG commitments, reduce the risk of fraud and unethical practices, and protect their reputations.
As a global leader in product origin verification, we have locations in Auckland, Dunedin, London and Washington DC.
Oritain is seeking a talented & experienced Statistical Data Scientist to join their innovative team in their modern Auckland CBD offices. We are looking for someone with a combination of skills in the following three vital and equally important technical areas that are required for this role: statistics and mathematics, machine learning and computing. If you have significant demonstrable evidence of these skills applied in a commercial environment, please read on.
Role Overview:
As a Statistical Data Scientist at Oritain, you will play a key role in developing innovative solutions to enhance existing products, enable new products and to support business decisions and strategies. You will work closely with other teams within Oritain to integrate Data Science solutions into existing workflows and systems.
Key Responsibilities:
- 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 visualisation's, including interactive maps and dashboards, as well as reports to communicate data 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 on data science projects.
Qualifications and Skills:
- Statistics & mathematics skills: You must have strong foundations in probability, statistics, uncertainty, linear algebra and calculus beyond first-year tertiary level and, preferably, have completed courses at post-graduate level. You must be confident and competent in using probability, statistics and mathematics to design and develop solutions for real-world problems that can be integrated into existing workflows and systems.
- Machine Learning skills: You must be proficient in working with large datasets, data transformations, data and metadata cleaning and maintenance. You much have demonstrable experience in applications of classification, clustering, dimension reduction and other machine learning methods and algorithms to produce useable outcomes, including rigorous quantitative assessment of performance.
- Computing skills: You must have strong programming skills, understanding of good programming practices, standards and paradigms and have experience working in a collaborative coding environment that is attentive to creating efficient and maintainable code. You must understand machine learning life cycles and machine learning operations and have an awareness of industry standard tools and practices in machine learning. You must have experience writing code that is efficient and optimised, for the development of research code and production code. You must have experience using software development tools such as VS Code, Conda and GitHub and other industry best-practice tools, standards and processes including environment management. You must have experience working with command line tools and Unix based operating systems. You must be conversant with Python and R, both for code development and deployment of machine learning models and algorithms in a cloud environment (preferably Azure), including writing code for parallel processing and distributed processing to scale up computations. You must have experience working with databases and with internal and external APIs (internal software, databases and cloud services). Experience in using other languages, such as HTML and JavaScript, is desirable but not essential.
- Soft skills: You must be upfront, open, teachable, able to learn and re-learn, have impeccable professional integrity, and aspire to high standards and personal excellence. You must have excellent problem-solving and analytical skills, attention to detail, and far-sightedness to anticipate global consequences of local actions. You must be able to adapt and keep up with the fast-paced technology environment. You must have the ability to work in a dynamic commercial environment where tight deadlines are common and can align technical and commercial requirements. You must be able to work effectively with others in cross-functional teams and collaborate with stakeholders from different disciplines. You must therefore have strong verbal and written communication skills, including the ability to communicate complex technical concepts to non-technical audiences.
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