Senior Fraud Prevention Analyst
7 days ago
Cuscal Limited is a leading Australian payments company that is committed to providing innovative payment solutions. Our team is passionate about driving the future of payments, and we're seeking an experienced Data Scientist to join our Financial Crime Team.
About the Role:We are looking for a highly skilled Data Scientist to help advance our Financial Crimes monitoring program. As a member of our team, you will be responsible for developing and implementing fraud detection and prevention strategies using machine learning and artificial intelligence.
You will work closely with our Senior Data Scientist to identify, prioritize, and undertake research and analytical activities leveraging all available data assets to help solve complex business problems.
Key Responsibilities:- Develop Cuscal's fraud detection and prevention strategies to stay ahead of emerging fraud trends and evolving threats.
- Formulate a coherent cross-business approach and strategic/tactical plan for big data initiatives.
- Conduct proactive, in-depth analysis of multiple data sets to prevent high-risk and financial crimes activity and emerging threats or optimize current monitoring across multiple channels.
- Develop and optimize predictive modelling software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large data sets from multiple disparate sources.
- Perform deep-dive analyses of experiments through reliable modelling methods that include numerous explanatory variables and covariates.
- Translate analytical insights into concrete, actionable business, process, or product improvement recommendations.
In return for your expertise, we offer a competitive salary range of AUD $120,000 - AUD $180,000 per annum, depending on experience, plus a range of benefits including flexible working hours, professional development opportunities, and a generous superannuation package.
About You:- University qualification in data science, computer science, statistics, or a related field.
- Demonstrated experience working with tools that deploy fraud rules and machine learning algorithms.
- Financial services experience in payments, card payments, acquiring, 3D secure, digital banking, and real-time payments. Experience in fraud and financial crimes is desirable.
- Understanding of relational databases and programming, including SQL, R, and Python.
- Experience interpreting data from visualisation tools such as PowerBI and visualisation libraries such as Matplotlib, Seaborn, and Plotly.
- Data mining of large data sets to identify emerging patterns, trends, and opportunities.
- Knowledge of natural language processing and large language models is desirable.
We offer a dynamic and inclusive workplace where talented individuals can thrive. Our hybrid work model provides flexibility and work-life balance, while our comprehensive benefits package includes education assistance, wellness programs, and career development opportunities.
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