Martin Burgess

Head of Product

Martin Burgess is the Head of Product at Nous Data Insights. He drives the development of impactful solutions that help clients make strategic decisions with lasting benefits.
Martin is an accomplished data science leader with a passion for creating innovative data products and empowering organisations with cutting-edge analytics. As a Head of Product at Nous Data Insights, Martin drives the development of impactful solutions that help clients make strategic decisions with lasting benefits.

Influential work

Martin’s expertise spans developing data products, advanced statistical analysis, and embedding data into decision-making processes. Across his career, he has:

  •  Led the development of data features that drove measurable growth in customer outcomes, such as increased revenue and engagement.
  • Designed proprietary data sets using advanced machine learning and statistical techniques to unlock valuable insights and intellectual property.
  • Guided organisations in adopting data-informed cultures, improving accessibility and empowering teams to make evidence-based decisions.
  • Delivered analytical projects for government and private sector clients, helping shape strategies and program designs to achieve positive outcomes.

Prior to Nous Data Insights

Before joining Nous Data Insights, Martin was Head of Data at Raisely, where he contributed to significant product improvements and business growth through data-driven strategies. Earlier, he served as Senior Data Scientist at Nous Group, leading analytics projects and capability-building initiatives.

Martin holds a Master of Statistics (with Excellence) and a Doctor of Philosophy (Neuroscience) from the University of New South Wales, as well as a Bachelor of Science (Advanced) (Hons I) in Neuroscience from the University of Sydney.

Outside of work

Martin enjoys running and exploring the Illawarra region with his young family. He is also passionate about mentoring others in data science and continuing to refine his expertise in statistical methodologies and machine learning applications.