Undergraduate Data Scientist/Mathematician (tempor...

Company:
Location: Newstead QLD

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Undergraduate Data Scientist/Mathematician

5 February 2021

Title Undergraduate Data Scientist/Mathematician

Reports to Product Manager – Data Science

Direct reports Nil

Division Corporate Services

Job type Temporary

Annual base salary $67,397.53 per annum excluding superannuation

Location Newstead, QLD

Closing Date Thursday 11 February 2021 at 5.00pm AEST

Who is the National Heavy Vehicle Regulator?

The National Heavy Vehicle Regulator (NHVR) commenced operations in 2013 as a national entity responsible for
regulating all vehicles in Australia over 4.5 tonnes gross vehicle mass. Located in Brisbane, the NHVR minimises the
compliance burden on the heavy vehicle transport industry, reduces duplication and inconsistencies across state and
territory borders, and ultimately for the heavy vehicle business with government in Australia.

What is important to us?

At the NHVR our workplace values set the tone for our organisational culture:

  • People matter
  • Customer first
  • We add value
  • Strong partnerships

We value staff with a genuine belief in the work they do and the benefit it will bring. We aim to develop a supportive
work environment which we believe will be achieved by a focus on professionalism, team work and collective values.

What do we expect of our employees?

The NHVR is seeking an individual who:

  • Is committed to meet and exceed the expectations of our clients and stakeholders
  • Is energised by identifying new approaches and solutions
  • Is innovative in addressing day-to-day challenges
  • Is supportive towards colleagues and contributes towards making their workplace an enjoyable place to be.

Commitment to safety, diversity and anti-discrimination

The NHVR is committed to providing a safe, forward-thinking and tolerant work environment. Diversity within our
workforce is valued as being representative of the standards, values and diversity within the community and clients we
serve.

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Position Description | Undergraduate Data Scientist/Mathematician

Environment

Through leadership and influence, the NHVR administers a national system that delivers consistent and streamlined
regulatory services and administration to the Australian heavy vehicle road transport sector, reducing regulatory burden
whilst enabling greater safety and productivity.

The Corporate Services Division enables NHVR to achieve its strategic vision through corporate governance, performance
improvement and the delivery of corporate functions and activities.

Primary Objectives

The undergraduate will have a broad understanding of the following to assist senior team members and stakeholder to
improve regulatory processes and outcomes. Detailed knowledge and applied experience is not expected at the
undergraduate level:

  • using data to for decision making
  • using mathematical models to test the effectiveness of different courses of action

Key Responsibilities/Accountabilities

  • Undertake a wide varity data science related activities (technical and non-technical) at the direction of senior
team members
  • Learn from technical and business SMEs and apply learnings in completing assigned tasks
  • Execute test plans based on the direction of senior team members
  • Complete assigned tasks to the agreed deadlines and proactively advising senior team members of progress,
issues and completion
  • Comply with WH&S policies and procedures and contribute and promote a safe and health work environment
  • Adhere to all NHVR policies and procedures to ensure compliance with NHVR internal processes.

Skills and Capabilities

  • Broad understanding of statistical techniques and concepts
  • Demonstrated analytical, problem-solving and lateral thinking with strong attention to detail
  • Demonstrated strong written and verbal communication skills
  • Demonstrated ability to work as part of a team of people.

Qualifications and Experience

Highly Regarded:

  • Currently enrolled in computer science, statistics, applied maths or related fields.
  • Knowledge of Microsoft statistical and data analysis tools such as Excel and PowerBI
  • Machine learning tools and platforms.

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