Principal Data Scientist

1 month ago


Wellington City, New Zealand New Zealand Government Full time

Te Amorangi Mātauranga Matua, the TEC - is a small Crown agency with a big job to do - ensuring New Zealanders have the skills and the knowledge they need to build a great life, and ensure New Zealand thrives. We invest over $3 billion annually across the tertiary education and careers systems.
If you're looking for your “why”, then come and join us at TEC. We truly believe in the transformational benefits of education and vocational training and as a result we invest $3 billion a year in tertiary education and training and seek to lift the aspirations and skill bases of all New Zealanders from ages 7 to 74.
It's an exciting time in the careers and education sector with large scale and meaningful change taking place.

**Mōhiohio**: Information Directorate
The Information Directorate delivers the ICT infrastructure and information tools to support the business and develops data, data products, information, and new tools for colleagues, customers, TEOs, and other agencies to support TEC's invest and champion goals.

**Raraunga me ngā Tātaritanga**: Data & Analytics
Data is key for TEC. The Data & Analytics team establishes and manages the data pipeline from data collections to data development and insights to support the core business systems to the level required by TEC and partner organisations. The Data & Analytics team is comprised of three teams grouped in centres of excellence: Data Collection, Data Development, Analytics.

**He angitūtanga**: About the Role
As a Principal Data Scientist, you will not only be the technical leader in TEC's data science practice, but able to guide junior staff members and form relationships across the business to use data to solve practical problems. You will:

- Work with the business to develop practical data science solutions to business problems
- Develop insights from complex data and present them to stakeholders
- Direct the creation and review of business-wide approach for generating value from data science and analytics
- Explore through an information lens, ways of using new technologies to change how we look at business problems and processes.

**He kōrero mōu: What we are looking for**:
This is an ideal opportunity who enjoys collaborating with other teams to address data quality issues, sharing results in a compelling way and in the process improving the use data across the organisation. You will bring the following:

- Experience working with business stakeholders to create data science solutions that work for them
- In-depth experience using statistical techniques
- Experience in using R, Python, SQL, Databricks
- Knowledge and experience using a variety of techniques to communicate data insights
- Up-to-date knowledge of trends in data science
- Experience using either Qlik Sense or PowerBI
- Ability to select techniques based on an extensive experience and knowledge of the strengths, weaknesses and expected performance of different approaches to machine learning, and establishes good practice in the development, evaluation, monitoring, and deployment of machine learning systems.

**Ngā āhuatanga kei a mātou**: What's in it for you
- Three additional (TEC Days) leave days
- A range of benefits including flexible working options, a wellness programme and the ability to purchase extra leave.
- A motivated and supportive manager, keen to make the most of your skill set
- Be part of a close-knit team who support each other
- Reduced premiums through our Health Insurance Group Scheme
- A focus on Career development and internal opportunities

The salary range for this position starts at $122,148 is up to $136,965+, which is negotiable depending on demonstrable skills and experience

**Me pēhea te tuku tono**: How to Apply
Applicants must have the ability to obtain and maintain the legal right to work in New Zealand.
Prior to the Tertiary Education Commission confirming any offer of employment, pre-employment checks will be undertaken including criminal conviction history and reference checking as a minimum.



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