Overview
Join a top-tier investment bank on a transformative journey to embed AI and advanced analytics into the core of its Wealth Management business in Asia. As a Senior Data Scientist / ML Engineer, you will play a dual role at the intersection of innovation, engineering, and strategy - developing and deploying scalable AI models while shaping the bank’s AI Center of Excellence (COE).
Working closely with the CDO, you’ll drive impactful AI initiatives that enhance hyper-personalization, client experience, and operational efficiency. This is an opportunity to build next-gen AI solutions while contributing to enterprise-wide digital transformation in a highly collaborative and innovative environment.
Key Responsibilities
- Build and deploy production-grade machine learning models across areas such as personalization, recommendation systems, client segmentation, credit risk, fraud detection, and churn prediction.
- Leverage advanced techniques, including deep learning, reinforcement learning, NLP, and generative AI (e.g., prompt engineering, RAG, agentic AI).
- Design end-to-end ML pipelines using cloud-native, scalable infrastructure (AWS, Azure, GCP) and MLOps best practices.
- Develop and maintain ML infrastructure and automation workflows to enable rapid experimentation, training, and deployment.
- Implement continuous monitoring, performance evaluation, and real-time model optimization.
- Work with Front Office, Marketing, Risk, Compliance, Credit, and IT teams to integrate AI into business processes and client-facing platforms.
- Collaborate with data engineers to build robust, scalable data pipelines and ensure data quality, consistency, and governance.
- Contribute to feature engineering, preprocessing, and real-time data workflows.
- Ensure AI models comply with internal policies and regulatory requirements (e.g., data privacy, fairness, explainability).
- Stay abreast of the latest trends in AI/ML and apply cutting-edge research to real-world problems.
- Share knowledge, mentor junior team members, and contribute to the upskilling of staff across the organization.
- Establish scalable workflows, governance models, and standards for AI model development and industrialization.
- Promote a culture of AI across the firm and collaborate under the Group’s approach with global entities.
Key Requirements
Education & Experience
- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Mathematics, or a related field.
- 5 - 8+ years of experience in data science and machine learning, including at least 2 years in a senior or lead role.
- Proven track record of deploying AI models in production, preferably in financial services, tech, or a highly regulated industry.
Technical Skills
- Proficient in Python, SQL, and at least one compiled language (e.g., Java or C++).
- Deep experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and MLOps tools (e.g., Docker, Kubernetes, Grafana, Prometheus, Giskard).
- Strong knowledge of big data tools (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Experience with streaming data, real-time ML, and model monitoring systems.
Domain Knowledge
- Ideally some experience in Financial Services, client behavior analytics, risk modeling, or fraud detection.
- Strong understanding of model interpretability and explainability (e.g., SHAP, LIME).
Soft Skills
- Strategic thinker with a hands-on mindset.
- Strong communication and stakeholder management skills.
- Ability to influence and collaborate across functions and geographies.
- With well over a decade of a solid and enviable track record behind us, headquartered in Hong Kong, Pinpoint Asia Infotech Pte Ltd (EA License: 16C8291) is the go-to IT Search Firm for several top Investment Banks and Financial Institutions.
If you are interested in the above position, please send your CV to Charlie Kim @ resume.sg@pinpointasia.com (EA Registration number: Reg No: R23112483)