Senior Data Scientist
Shift
Full-time
On-site
North Sydney New South Wales Australia
Company Description
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.
Job Description
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.
What You’ll Do:
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
Qualifications
What You'll Bring:
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
Bonus points if you have:
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
Additional Information
Key Benefits:
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.
#LI-Hybrid
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.
Job Description
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.
What You’ll Do:
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
Qualifications
What You'll Bring:
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
Bonus points if you have:
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
Additional Information
Key Benefits:
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.
#LI-Hybrid