• 1Search for courses by Study Area, Level and Location
  • 2We deliver you all the matched results
  • 3Choose one or more course providers to contact you

Distance from location (kms)

Exact 5 10 25 50 100

Posted since

All 2 Days 1 Week 2 Weeks 1 Month

Sort results by

Relevance Date



Data Scientist

Private Company - Sydney, NSW

Source: uWorkin

Source: uWorkin


An incredibly dynamic established business that researches and builds predictive analytics for sports, using advanced techniques and technologies. They research and model all aspects of gameplay to derive unique insights into a variety of sports. Their analytics provide the core of sports trading systems in competitive, time-sensitive markets around the world.

Based in Sydney CBD, where a talented group of data scientists, engineers, and sports specialists work together to build our unique products. They offer a working environment designed to attract and retain exceptional people; colleagues to learn from and be inspired by, an informal working environment with the tools and facilities required to do the job well, and a healthy approach to work-life balance. They greatly value the diversity of all kinds and are committed to a flexible, respectful working environment.

Successful team members share the following characteristics:
Technical excellence in statistics, machine learning, or computer engineering
A passion for sports data and analytics.
Accountability to the team in a fast-moving environment.
Exceptional communication skills.
A pragmatic, get it done style.

Data Scientists:
Develop new predictive approaches and models for our target sports (soccer), using a variety of tools, including standard statistical, probabilistic programming, and neural networks.
Work with specialists on feature development, and with clients on model utility (i.e. low bias predictive performance), with a continuous improvement mindset for operational models.
Define and build data pipelines to drive modelling.
Define and build tests and reports on input data integrity (including statistical checks on e.g. covariance), and predictive performance, likely creating custom approaches to do so.
Work within professional best practice for model development, including test automation and version control.
Adhere to the very strictest standards for IP protection and security.

PhD or equivalent professional experience in either Maths, Statistics, Computer Science (AI/ML) or other relevant quantitative fields.
Proficient in machine learning tools and approaches.
Proficient in R, python, SQL among others scripting and programming languages.
Familiarity with public cloud computing (AWS, Google, Azure) would be an advantage.

Research and/or industry experience in machine learning (Bayesian prob. modelling, neural nets among others), feature selection, statistics
Industry experience is not a requirement, we invite applications from qualified candidates still working in research/academia.
Minimum 2 years’ experience in data science projects which requires working with high dimensional/big data.
Preferable to have scientific background in working with small n and large p datasets.
Research experience in exploratory data analysis
Desire to innovate and bring scientific rigor to modelling.

$100,000 - $130,000 + superannuation dependant on experience

For more details please contact Steve Grace