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Help shape Deloitte's statistical modelling capability across credit risk, model validation and AI in financial services.
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Tackle big issues like cyber, trust, resilience and digital transformation
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Mentoring, coaching and leadership programs to help you make an impact that matters
This is a Senior Manager opportunity in the Sydney team to lead complex statistical modelling work that helps major financial institutions make better credit risk and AI-driven decisions.
What will your typical day look like?
In this role, you'll lead statistical modelling, validation and performance assessment across credit risk use cases including PD, LGD and EAD. That could mean testing model design, interrogating large and complex datasets, or assessing calibration, discrimination, stability, robustness, uncertainty and bias.
A big part of your impact will come from helping clients build confidence in the models they rely on for lending, provisioning, capital and broader risk management. You'll also review machine learning and AI models used in financial decision-making, bringing a clear lens to explainability, monitoring and responsible use.
Working closely with clients, internal stakeholders and junior team members, you'll guide high-quality delivery while helping grow Deloitte's capability in this space. The work is technically deep, commercially relevant and varied enough to keep you learning as the market continues to evolve.
About the team
Deloitte's Assurance practice helps clients build confidence in their systems, models and decision-making. Within that, this team applies statistical analysis, quantitative modelling and model assessment to support financial institutions with traditional credit risk models as well as emerging AI-enabled use cases. It's a space where strong technical thinking, practical industry context and growing demand for responsible AI all come together.
Enough about us, let's talk about you
You may have all or some of the following skills/experiences:
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Experience in statistical modelling, data analysis, model testing and interpreting quantitative results
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Background in credit risk, financial risk or another complex modelling environment
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Hands-on experience with PD, LGD and EAD model development, review or validation
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Capability in Python, R, SAS, SQL or similar analytical tools
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Strong understanding of model performance measurement, statistical testing approaches and model limitations
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Confidence explaining complex statistical concepts and findings to both technical and non-technical audiences
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Experience leading projects, mentoring team members and maintaining quality across deliverables
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Nice to have: exposure to machine learning or AI model testing, monitoring, explainability, bias assessment, stress testing, climate-related credit modelling or NLP
Why Deloitte?
At Deloitte, we focus our energy on interesting and impactful work. We're always learning, innovating and setting the standard; making a positive difference to our clients and our society. We put coaching at the heart of what we do, helping our people grow their careers in any direction - whether it be up, moving into something new, or even moving across the world.
We embrace diversity, equity and inclusion. We have a diverse collection of people from different backgrounds, with different experiences, gender identities, abilities and thinking styles. What binds us together is a shared commitment to value everyone's perspective and to cultivate inclusion; so that our work environment is a safe space we can all belong.
We value in-person connection with our clients and our colleagues. We offer several ways for you to work flexibly so that you can serve your clients, stay connected with your team, and manage your personal priorities.
We help you live and work well. To support your personal and professional life, we offer a range of perks and benefits, including retail discounts, wellbeing leave, paid volunteering days, twelve flexible working options, market-leading parental leave and return to work support package.
Next Steps
Sound like the sort of role for you? Apply now, we'd love to hear from you!
