job description
Join the Monetary Authority of Singapore (MAS) as a Senior Data Scientist (AI/ML) and work remotely from the vibrant hubs of Bali—Canggu, Ubud, Denpasar, and beyond. This is a unique opportunity to leverage cutting-edge artificial intelligence and machine learning to uncover deep insights, develop innovative data products, and drive tangible business value for one of Asia’s most respected financial institutions.
In this role, you’ll collaborate with cross-functional teams to transform complex datasets into actionable strategies, shaping the future of financial regulation and fintech innovation. Whether you’re optimizing risk models, automating compliance processes, or building predictive analytics tools, your work will have a direct impact on Singapore’s financial ecosystem—all while enjoying the work-life balance of Bali’s tropical paradise.
Ideal for experienced data scientists passionate about AI-driven solutions, this contract position offers the flexibility of remote work with the prestige of contributing to a world-class central bank.
Responsibility
- Design, develop, and deploy AI/ML models to solve complex financial and regulatory challenges.
- Lead end-to-end data science projects, from hypothesis generation to production implementation.
- Collaborate with stakeholders to identify high-impact use cases for predictive analytics, NLP, or computer vision.
- Optimize and scale existing machine learning pipelines for performance and efficiency.
- Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and business opportunities.
- Develop automated reporting and dashboarding solutions for real-time decision-making.
- Ensure compliance with data governance, security, and ethical AI standards.
- Mentor junior team members and share best practices in data science and MLOps.
Qualifications
- 5+ years of experience in Data Science, AI, or Machine Learning, preferably in finance or regulatory sectors.
- Master’s or PhD in Computer Science, Statistics, Mathematics, Economics, or a related field.
- Proficiency in Python, R, SQL, and frameworks like TensorFlow, PyTorch, or scikit-learn.
- Experience with big data technologies (e.g., Spark, Hadoop, Databricks) and cloud platforms (AWS, GCP, Azure).
- Strong background in statistical modeling, hypothesis testing, and experimental design.
- Familiarity with financial data (e.g., transactional, market, or risk data) is a plus.
- Excellent communication and storytelling skills to translate technical insights for non-technical audiences.
- Ability to work independently in a remote setting with a results-driven mindset.