Machine Learning Fraud Prevention Specialist

2 weeks ago

Sydney, New South Wales, Australia beBeeMachine Full time $100,000 - $120,000
Machine Learning Fraud Prevention Specialist

This is an exciting opportunity to join our team in shaping the future of fraud detection. As a Machine Learning Fraud Prevention Specialist, you will play a key role in developing and deploying advanced models to prevent revenue leakage across various monetisation channels.

About the Role:

  • Developing and deploying machine learning models to detect and prevent fraudulent activities.
  • Collaborating with cross-functional teams to build and iterate on fraud prevention strategies.
  • Shaping our fraud ML strategy, using a strong product mindset.
  • Architecting, building, and maintaining ML systems that underpin fraud detection and response.
  • Mentoring and upskilling engineers and data scientists in the team.
  • Advocating for ethical AI practices and user trust in our fraud prevention approaches.

Required Skills and Qualifications:

  • Built and deployed machine learning models in production environments (preferably for fraud, abuse, or anomaly detection use cases).
  • Comfortable working across the ML lifecycle – from data wrangling to evaluation and model iteration.
  • Operate strategically—not just building what's asked, but shaping what should be built.
  • Strong product sense and empathy for both internal and external users.
  • Effective communication and alignment skills to drive clarity in complex problem spaces.
  • Familiarity with tools like PyTorch, TensorFlow, or scikit-learn.

Benefits:

  • Opportunity to work on cutting-edge fraud detection projects.
  • Chance to shape the company's fraud prevention strategy.
  • Collaborative and dynamic work environment.
  • Ongoing training and professional development opportunities.

Other Information:

  • The Revenue Fraud Prevention team is responsible for understanding how our business attracts fraud and finding effective ways to manage it.
  • We work closely with other teams around the company to achieve our goals and maintain business integrity.

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