Key Duties/Responsibilities: 

• Design and develop machine learning models to detect and prevent Payments Fraud, in Realtime and Near Realtime.
• Contribute to every phase of the Data Science workflow, from data preprocessing to model deployment and monitoring/evaluation.
• Write clean, reusable, and scalable code using OOP techniques to integrate models seamlessly into a production environment.
• Handle and manipulate large, complex datasets, ensuring proper data preprocessing, transformation, integration, and enrichment for high-quality model training and evaluation.
• Conduct in-depth data analysis to uncover new fraud patterns, identify ways to tackle them, and present actionable insights internally and to clients.
• Monitor, evaluate, and continuously improve the performance of models deployed in production.
• Train and empower clients to leverage models effectively, ensuring maximum value from our platform.

Key Skills/Experience: 

• Degree (BSc/MSc) in Data Science, Computer Science, or a related field.
• Solid understanding of Machine Learning principles and statistics.
• Background in Software Development will be considered a significant advantage.
• Experience with Cloud and Big Data technologies is a plus.
• Analytical mindset with excellent problem-solving skills and attention to detail.

Key Benefits: 

• Thorough training in all technologies involved.
• Primary focus on work-life balance.
• Flexible working hours.
• Hybrid working options.
• Competitive salary.
• Contribution to Provident Fund and Medical Fund.

To apply for this vacancy, please send your CV, along with any covering letter to [email protected] quoting the above job title. Please note that due to the high volumes of applications received only shortlisted applicants will be responded to. By sending us your CV you are giving CareerFinders your consent to be contacted for this and any other suitable vacancies that we believe match your skills and experience. To view our privacy policy, please click www.careerfinders.com.cy/privacy-policy.