Senior Data Scientist

Who is Shift?

At Shift, we're business specialists dedicated to helping Australian SMEs take control of their cashflow, streamline trade terms and choose the right financial products.

We believe Australian businesses are the driving force behind our economy and are core to our communities. That's why our business expertise, focus on relationships, and market-leading technology is at the core of everything we do.

Our unique approach to product innovation combined with our collaborative culture means you can build your career in a supportive environment. You'll be joining a diverse team of over 250 people who are always looking to deliver better outcomes for Australian businesses.

Join Shift as a Senior Data Scientist and drive the future of our analytics capabilities. You'll work closely with leadership, product and risk teams to build and deploy advanced statistical and machine learning models that power credit risk assessment, fraud detection, and profitability strategies. Your expertise will directly shape business decisions, optimise credit processes and elevate the team through mentorship and innovation.

• Partner with executive, product, risk, and frontline teams to define analytical goals and manage projects end-to-end, ensuring business alignment and executive buy-in

• Design, develop, and validate a comprehensive suite of models including credit risk (PD, LGD, EAD), provisioning (AASB/IFRS9), fraud, servicing, and profitability

• Translate complex statistical concepts into clear business insights and communicate effectively across stakeholders

• Optimize credit strategies, policies, automation, and decision-making through robust modelling and reporting

• Continuously improve machine learning architecture and research new techniques to drive innovation and performance

• Develop and deploy models in Python, collaborating with technology teams to ensure production integrity

• Validate and maintain the integrity of diverse data sources such as bank statements, credit bureaux, and financial reports

• Oversee model monitoring, governance, and reporting for internal, executive, and risk stakeholders

• Coach and mentor junior team members, fostering knowledge sharing and team development

• 4+ years experience developing and deploying predictive and machine learning models in a business environment

• Strong proficiency in Python and SQL, with hands on experience in model deployment and working with ML architectures

• Knowledge of credit risk modelling, including scorecards, behavioural models (PD, LGD, EAD), provisioning (AASB/IFRS9) and collections models

• Experience validating model inputs and ensuring data quality from diverse sources (bank statements, credit bureaux, financials, OCR)

• Excellent communication and presentation skills with the ability to translate complex analytics into clear business insights for senior stakeholders

• Proven project management skills, capable of scoping, planning and delivering analytics projects aligned with business goals

• Collaborative problem solver who thrives in cross-functional teams and drives innovation

• Advanced degree (Masters or PhD) in quantitative disciplines like Statistics, Mathematics, Computer Science, Finance, Economics, or Engineering

• Experience in business or commercial finance industries

• Exposure to credit/product strategy design and optimisation

• Expertise in provisioning model development and validation (IFRS9)

• Familiarity with deploying models in clustered computing environments like Databricks

• Experience engaging and influencing senior stakeholders across diverse business units

• Collaborative teams – a flat structure means everyone can learn from colleagues and senior leaders around the business.

• Be involved – come together with all of your colleagues every 100 days to share the product and technology roadmap and business strategy.

• Flexible working environment – we're headquartered in North Sydney with state-based workplaces and offer a flexible work policy.

• Family support – industry leading 26 weeks paid parental leave.

• Varied workspaces – our office enables areas for collaboration, brainstorming and socialising as well as focus zones.

• Range of benefits – supporting your physical, psychological and financial wellbeing.

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