Job description

Job no: 503687
Work type: Full-time
Location: Sydney, NSW
Categories: Information Technology, Research Administration support

Data Scientist - NDARC

Employment Type: Full-time (35-hour week)

Duration: 12-month Fixed Term role

Remuneration: $99K - $125K (dependent on experience) plus 17% superannuation and leave loading

Location: Randwick NSW

  • Be part of a team that’s delivering change at scale
  • Join one of Australia’s Top 20 most attractive employers
  • Thrive on a campus that’s buzzing with the energy of people doing great things

UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a community doing great things. But what makes us different isn’t what we do, it’s how we do it. Together, we are driven to be thoughtful, practical, and purposeful in all we do.

Why your role matters

As the Data Scientist, you will be responsible for strengthening and expanding the study of novel online data sources to identify emerging trends in illicit drug use, markets and associated behaviours for the Drug Trends program at the National Drug and Alcohol Research Centre (NDARC). The role will include expanding existing monitoring and reporting on darknet cryptomarket sale of illicit drugs, establishing new reporting on other online sources (e.g., internet discussion forums, social media platforms such as Reddit and Twitter, search engines) and building online interactive visualisations to interrogate and share findings. Drawing upon an array of computational and statistical skills, you will collaborate with leading figures in this field to address critical public health questions in relation to substance use.

The Data Scientist reports to the Senior Research Fellow and has no direct reports. Please see attached Position Description for full details.

Who you are

To be successful you must have:

Level 7:

  • Relevant degree specialising in computer science, mathematics, biostatistics, data science, statistics, or other quantitative discipline, with relevant experience or equivalent competence gained through any combination of education, training and experience.
  • Demonstrated experience in using Python for web scraping, data cleansing, and machine learning. Knowledge of other programming languages such as R would be advantageous.
  • Demonstrated experience in building, testing and deploying machine learning models (GLM, Random Forest, GBM, Neural networks etc).
  • Demonstrated experience in cleaning, merging, and managing large data sets, including implementing various strategies to maximise data integrity.
  • Demonstrated experience in building online data visualisation platforms (e.g., Tableau, R Shiny).
  • Excellent written and verbal communication skills, with a high level of attention to detail.
  • An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
  • Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

Level 8 (in addition to the above):

  • Doctoral degree in computer science, statistics, biostatistics, data science, mathematics, or other quantitative discipline, with substantial extension of the theories and principles normally requiring extensive relevant experience.
  • Demonstrated capacity to conceptualise novel research questions and carry out independent research as indicated by a proven track record of leading reports or manuscripts for publication in peer-reviewed journals.
  • Demonstrated evidence of bringing innovation and improvements in achieving core objectives and outputs.

Please apply online - applications will not be accepted if sent to the contact listed.

Contact (For job related queries only):

Jamie Cutler: Talent Acquisition Coordinator E:

Applications close: Sunday 5th December at 11:55pm

Find out more about working at UNSW at

UNSW aspires to be the exemplar Australian university and employer of choice for people from diverse backgrounds. UNSW aims to ensure equality in recruitment, development, retention and promotion of staff, and that no-one is disadvantaged on the basis of their gender, cultural background, disability, sexual orientation or identity. We encourage everyone who meets the selection criteria to apply.

Position Description

Advertised: 16 Nov 2021 AUS Eastern Daylight Time
Applications close: 05 Dec 2021 AUS Eastern Daylight Time

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