Senior Data Scientist

Posted Yesterday
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Sydney, New South Wales, AUS
Hybrid
Senior level
Financial Services • Cybersecurity
Moving Payments Forward. Together.
The Role
Lead advanced analytics and fraud detection initiatives within the Financial Crimes domain. Develop, deploy, monitor, retrain, and govern machine learning models using large datasets and production-grade MLOps practices. Translate analytical findings into business recommendations, collaborate with Product, Technology, Risk, Fraud Operations, and Engineering teams, evaluate emerging technologies, and mentor data scientists.
Summary Generated by Built In
Company Description

Forward with Cuscal

Ever tapped your phone to buy a morning coffee or made a purchase from your favourite online store? Chances are, we've made it happen.

At Cuscal, we've been at the forefront of payments innovation for nearly 60 years, enabling seamless, secure solutions that millions of Australians rely on every day. From launching Australia's first ATM to helping shape the future of digital payments, we continue to transform the way money moves.

Job Description

Your Opportunity

As a Senior Data Scientist, you will support the data science function within the Financial Crimes Domain. You will leverage large and complex data sets to uncover insights, build predictive models and influence strategic decision-making across the business.  You will also play a key role in driving data science best practices, mentoring team members and advancing the organisation's fraud detection and prevention capabilities.

You'll make an impact in this role by:

  • Leading the development of advanced analytics, machine learning models and fraud detection strategies to identify and mitigate emerging fraud risks.
  • Driving the end-to-end machine learning lifecycle, including feature engineering, model deployment, monitoring, retraining and governance to ensure scalable, reliable and well-managed production outcomes.
  • Working with large, complex and diverse datasets to uncover patterns, validate hypotheses and generate actionable insights.
  • Translating complex analytical findings into practical recommendations that improve products, processes and business outcomes.
  • Driving best practice across data science, experimentation, machine learning, MLOps and analytics frameworks.
  • Evaluating emerging technologies, tools and methodologies to enhance fraud detection effectiveness and operational efficiency.
  • Partnering with cross-functional stakeholders including Product, Technology, Risk, Fraud Operations and Engineering teams to deliver data-driven solutions.
  • Mentoring, coaching and providing technical guidance to junior and intermediate Data Scientists, fostering capability uplift and professional development across the team.

Qualifications

What you'll bring

To be successful in this role, you will bring a combination of the following skills, experience and capabilities:

  • Extensive experience developing and deploying machine learning, artificial intelligence, statistical modelling and advanced analytics solutions to solve complex business problems and deliver measurable outcomes.
  • Experience working within Financial Services, payments, acquiring, digital banking, financial crime, fraud risk management or real-time payments environments.
  • Advanced programming skills in Python and SQL, with experience developing scalable data science and machine learning solutions.
  • Proven experience designing, developing, validating and optimising machine learning models across the full model development lifecycle.
  • Hands-on experience with Databricks or similar cloud-based data science and machine learning platforms, including model development, data engineering workflows and productionisation of machine learning solutions.
  • Strong understanding of MLOps principles and practices, including CI/CD pipelines, automated testing, model deployment, model monitoring, performance tracking, retraining and governance.
  • Experience working with cloud-based data, analytics and machine learning ecosystems and delivering production-grade AI and ML solutions.
  • Experience working with large, complex and diverse structured and unstructured datasets to identify fraud trends, risks and opportunities.
  • Strong stakeholder engagement and communication skills, with the ability to translate complex analytical concepts and model outputs into business outcomes
  • Demonstrated experience mentoring and developing junior Data Scientists.

Additional Information

Why Cuscal?

At Cuscal, you’ll experience interesting work that’s transforming. You get the security of an established organisation and the energy of a company committed to innovation. For 60 years, we’ve set the standard in payments, and now we’re preparing to redefine it for the future. 

You’ll also enjoy a range of benefits, including: 

  • Recognition and growth: Celebrate achievements through IGNITE and grow with tailored development opportunities
  • Wellbeing focus: We support your physical, mental and financial health with holistic initiatives and access to discounts via Cuscal Advantage
  • Diversity and inclusion: Join a workplace that values different perspectives and flexible work arrangements

If you’re excited about this opportunity, we’d love to explore how you can contribute to our vision. Applications may be reviewed as they’re received, so don’t wait - apply now.

Cuscal is an equal opportunity employer committed to creating a diverse, inclusive and barrier-free workplace. We welcome applications from Aboriginal and Torres Strait Islander peoples, people living with disability, LGBTQIA+ communities and individuals from culturally diverse backgrounds.

Note: Cuscal does not accept unsolicited resumes from recruitment agencies or search firms. 

Skills Required

  • Extensive experience developing and deploying machine learning, artificial intelligence, statistical modeling, and advanced analytics solutions.
  • Experience in financial services, payments, acquiring, digital banking, financial crime, fraud risk management, or real-time payments.
  • Advanced programming skills in Python and SQL.
  • Experience designing, developing, validating, and optimizing machine learning models across the full model development lifecycle.
  • Hands-on experience with Databricks or similar cloud-based data science and machine learning platforms.
  • Strong understanding of MLOps, including CI/CD pipelines, automated testing, deployment, monitoring, performance tracking, retraining, and governance.
  • Experience with cloud-based data, analytics, and machine learning ecosystems and production-grade AI and ML solutions.
  • Experience working with large, complex, and diverse structured and unstructured datasets.
  • Strong stakeholder engagement and communication skills, including translating analytical concepts and model outputs into business outcomes.
  • Demonstrated experience mentoring and developing junior data scientists.
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The Company
HQ: Sydney, New South Wales
704 Employees
Year Founded: 1966

What We Do

Cuscal is a payments and regulated data services provider in Australia. Since 1966, we have enabled Australian banks, mutuals, corporates and fintechs to better serve and connect with their customers through the implementation of innovative technology solutions. Our vision: To transform the future of how money moves and how Australia does business. Our purpose: To enable competition and power progress, one transaction at a time. We deliver this through our expert team, our ability to anticipate and our deep understanding of the financial payments industry. Our proud history of firsts as the leader in payments solutions has made us the trusted partner for banks, mutuals, fintechs and corporates.

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