Senior Data Scientist – Fraud Detection & Machine Learning

Location: Perth (flexible, with hybrid full remote options)

Salary: Up to $220k + super

The Opportunity

We’re searching for a Senior Data Scientist who thrives in high-scale, constantly evolving environments. You’ll step in to support an overloaded but brilliant Data Science lead and work alongside a junior team member. Together, you’ll be tackling the challenge of fraud detection and prevention across digital channels, applying advanced machine learning techniques to massive datasets.

This role is about impact: building models, detecting patterns, and solving problems that shift as fast as the fraudsters adapt.

What You’ll Do

• Lead and contribute to the design, build, and optimisation of fraud detection pipelines.
• Apply both supervised and unsupervised ML techniques to uncover new fraud types.
• Work with tools and environments such as BigQuery, Python, TensorFlow, PyTorch, scikit-learn (open to variations as long as outcomes are delivered).
• Partner with senior stakeholders — Heads of Data Science, Engineering, and Product — to deliver high-value, production-ready solutions.
• Mentor and support junior data scientists, shaping the team’s technical excellence.

Must-haves:

• Strong background in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with BigQuery and large-scale data environments.
• Demonstrated expertise in fraud detection, anomaly detection, or related high-volume transaction analysis (finance industry experience highly regarded).
• The ability to communicate complex technical insights clearly to both technical and non-technical audiences.

Nice-to-haves:

• Familiarity with digital ad ecosystems (Google, Meta, TikTok, programmatic).
• Broader exposure to GCP stack (Airflow, dbt).

Who You Are

• Deeply technical, but also able to tell the story of the data.
• Resilient and adaptable - you know today’s solution may need to evolve tomorrow.
• A team player who values execution, commitment, and delivering on promises.
• Someone who thrives in a relaxed but high-performing environment.

Why Join?

• High-impact work: tackle complex fraud challenges on datasets in the millions.
• Innovation-driven culture: ongoing investment in AI tools and infrastructure.
• Flexibility: hybrid working with just a couple of days in the office.
• Growth: mentoring, internal mobility, and clear progression pathways.
• Work hard, play hard: a collaborative, energised team that values results and fun.

The Process

1. Initial interview with Data Science & Engineering leadership (1 hour).
2. Practical exercise.
3. Presentation & discussion with CPO.
4. Final chat with executive leadership.

📩 Ready to apply?

If you’re passionate about applying machine learning to solve real-world fraud challenges and want to work in a team that balances deep technical expertise with a fun, forward-thinking culture — we’d love to hear from you.