Manager, Data Science

About Us

UniSuper is a workplace where highly skilled professionals are empowered to Think Great and deliver exceptional retirement outcomes for our members. With a culture grounded in accountability, collaboration and care, your work contributes directly to members’ long-term financial security.

Our Data Office helps UniSuper unlock the value of data, analytics and insights to support better decision making and improved member outcomes.

Help shape how UniSuper applies data science by turning sophisticated modelling and analytical outputs into practical decisions and measurable outcomes.

The role

As Manager, Data Science, you’ll lead UniSuper’s data science capability and a small team of specialists delivering machine learning, predictive modelling and advanced analytics solutions.

This is more than a people leadership role. You’ll bring the technical credibility to guide and challenge modelling approaches, alongside the commercial judgement to determine where data science can create genuine value. You’ll work directly with senior stakeholders to understand complex business problems, translate them into analytical opportunities and ensure outputs lead to practical decisions and measurable outcomes.

You’ll be accountable for the end-to-end application of data science, from selecting the right problems and overseeing model development through to governance, stakeholder adoption, ongoing performance monitoring and assessment of real business impact. Furthermore, you will: 

• Lead, coach and develop a team of data science specialists.
• Set the technical direction, methodologies and standards for data science modelling.
• Lead the development, production and ongoing maintenance of predictive and propensity models.
• Translate complex model outputs into clear recommendations that senior stakeholders can understand and act on.
• Partner with business leaders and Product Owners to identify where data science can address operational, regulatory and strategic challenges.
• Challenge whether proposed analytical solutions are practical, commercially valuable and appropriate for the business problem.
• Establish strong model governance, including validation, documentation, performance drift, bias and fairness monitoring.
• Measure whether models and insights are delivering meaningful business outcomes, not simply technical performance.
• Oversee feature requirements, production scoring and the ongoing performance of models used by business stakeholders.
• Provide analytical leadership supporting financial crime risk, operational efficiency and regulatory obligations.
• Prioritise the team’s work across competing demands and make clear resourcing and delivery decisions.

About you

You’re an established data science or advanced analytics leader with deep experience applying predictive models in a complex business environment.

You can operate confidently at both the technical and commercial levels. You’re able to challenge data scientists on model design and performance, then communicate the implications clearly to senior stakeholders. Most importantly, you have demonstrated that your work has influenced decisions, changed how a business operates or delivered measurable value.

This role requires:

• Proven experience leading and developing a team of data science specialists.
• Substantial hands-on experience in data science, predictive modelling or machine learning before moving into leadership.
• Demonstrated experience developing, implementing and maintaining customer or member propensity models in a production environment.
• Leading data discovery and partnering with business stakeholders to identify what is viable and meaningful within our data before we build. This may include data profiling, statistical analysis and rapid prototyping.
• Evidence of translating model outputs into practical business decisions and measuring the resulting outcomes.
• Strong technical knowledge of modelling methodology, feature development, model validation and performance monitoring.
• Experience with model governance, including methodology documentation, drift monitoring, bias and fairness.
• Advanced stakeholder engagement skills, including the ability to influence senior leaders and communicate complex findings clearly.
• Experience evaluating analytical opportunities through a commercial, operational and risk lens.
• Intermediate to advanced capability across Python and machine learning, with experience in Azure, MLOps or CI/CD environments.
• Experience managing multiple analytical priorities within a complex and regulated organisation.
• Financial crime and fraud literacy.  
• Experience within financial services, banking, insurance or superannuation will be highly regarded. An actuarial background may also be relevant where it is supported by strong contemporary data science capability, production modelling experience and demonstrated commercial application.

What We Offer

UniSuper believes that the best way to achieve great things is when we come together and collaborate. Therefore, we ask you to be able to commit to 60% of your time in office.

UniSuper is proud of our culture and benefits, which empower our people to achieve their full potential, thrive, and grow their career with us. These include:

• 20 weeks paid parental leave
• $1,500 annual development budget
• 17% superannuation contribution
• Additional paid leave days

It should go without saying, but at UniSuper, we value and celebrate diversity and inclusion. We believe that a variety of perspectives, backgrounds, interests, abilities, and skills is crucial for delivering great retirement outcomes for our members. We invite you to apply for the roles that suit your career aspirations, even if you don’t meet all the requirements.