Deskripsi Pekerjaan
Monee is a leading digital payments and financial services provider in Southeast Asia, with a growing presence in Latin America. Our mission is to drive financial inclusion through innovative technology. We are currently looking for a talented Machine Learning Engineer - Risk Data to join our dynamic team in Singapore. In this pivotal role, you will be at the forefront of our risk management strategy, designing and implementing sophisticated machine learning models to detect fraud, assess credit risk, and optimize transaction flows. You will work with massive datasets to uncover hidden patterns and build predictive systems that safeguard our platform and our users. If you are passionate about applying cutting-edge AI techniques to solve real-world financial challenges, we want to hear from you.
Tanggung Jawab
- Design, develop, and deploy scalable machine learning models for risk assessment and fraud detection.
- Analyze large-scale financial and transactional data to identify trends, anomalies, and potential risks.
- Collaborate with data engineers to optimize data pipelines and ensure high-quality data availability.
- Monitor model performance in production environments and iterate on algorithms to improve accuracy and reduce false positives.
- Work closely with product managers and business stakeholders to translate complex requirements into robust technical solutions.
- Conduct rigorous A/B testing and statistical analysis to validate model impact and business value.
- Stay updated on the latest research in machine learning, risk management, and fintech technologies.
Kualifikasi
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 3+ years of professional experience in machine learning, data science, or a similar technical role.
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and deep learning frameworks (TensorFlow, PyTorch).
- Experience with SQL and NoSQL databases for data extraction and manipulation.
- Deep understanding of statistical modeling, risk management principles, and financial fraud patterns.
- Experience in the fintech, payments, or banking industry is a strong advantage.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.