Senior Applied Data Scientist

WHO WE ARE: As Singapore’s longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires. Today, we’re on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia’s leading financial services partner for a sustainable future. We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career. Your Opportunity Starts Here. Why Join Unlock the power of data to drive business growth and customer satisfaction. As a Data Analyst at OCBC, you'll play a critical role in helping us make informed decisions and stay ahead of the competition. With a strong focus on innovation and customer-centricity, you'll have the opportunity to work with cutting-edge technologies and collaborate with cross-functional teams to drive business outcomes. How you succeed To succeed in this role, you'll need to be a data-driven problem solver with a passion for analysis and insights. You'll work closely with stakeholders to understand business needs and develop data-driven solutions to address them. Your ability to communicate complex data insights effectively will be key to driving business decisions and outcomes. What you do • Drive the application of data science, advanced analytics, machine learning, conventional AI and generative AI to address business challenges and create measurable value for customers and the business. • Partner closely with business stakeholders to identify high-impact opportunities where data, analytics and AI can enhance customer experience, improve decision-making, strengthen risk management and drive business growth. • Translate business objectives and problem statements into analytical frameworks, machine learning models and AI solutions, ensuring alignment with business priorities and outcomes. • Generate actionable insights across the SME customer lifecycle, from start-up and early-stage businesses to established mid-sized and large enterprises, supporting customer acquisition, deepening, engagement and retention strategies. • Conduct in-depth analysis of customer transactional behaviour, network relationships, borrowing patterns and evolving financial needs to uncover growth opportunities and emerging risks. • Design, develop, validate and enhance machine learning, deep learning and AI models to support use cases such as customer propensity modelling, next-best-action recommendations, fraud detection, risk assessment and customer needs anticipation. • Evaluate and incorporate emerging AI and data science techniques, including generative AI capabilities, to improve business processes, customer interactions and operational effectiveness. • Collaborate with cross-functional teams and Group Data Office to deploy models into production and ensure ongoing monitoring, governance and performance optimisation. • Partner with Data Engineering teams to identify, source, curate and integrate internal and external datasets required for scalable analytics, model development and AI solutions. • Contribute to the development of the bank's Data & AI capabilities by promoting best practices in model development, responsible AI, experimentation and data-driven decision-making. Who you are • Postgraduate degree in Statistics, Mathematics, Computer Science, Software Engineering, Data Science, or a related quantitative discipline. • Minimum 10 years of experience in Data Science, Customer Analytics, Machine Learning, or AI solution development, with a strong track record of delivering measurable business outcomes. • Proven expertise in manipulating large and complex datasets, developing statistical models, and applying advanced analytics to solve business challenges. • Strong hands-on programming skills, with a solid understanding of software engineering principles, AI/ML architecture, design patterns, and production-grade development practices. • Experience working with large-scale and distributed data platforms and technologies, including Hadoop, Trino, Vector Databases (e.g., Elastic), and Ray. • Experience in designing, training, deploying, monitoring, and optimizing Machine Learning and Generative AI solutions in production environments at scale. • Exposure to Large Language Model (LLM) fine-tuning, distillation, Retrieval-Augmented Generation (RAG), and AI application development would be advantageous. • Knowledge of AWS Cloud and AI services, including Amazon Bedrock, SageMaker AI, EKS, EC2 GPU instances, S3, IAM, CloudWatch, and PrivateLink, would be an advantage. • Strong understanding of CI/CD, MLOps, and DevOps practices, with hands-on experience using tools such as Git/Bitbucket, Jenkins, and Jira. • Demonstrated ability to diagnose and resolve platform, model, and pipeline issues, including performance bottlenecks, infrastructure incidents, model drift, and operational anomalies. • Strong communication, presentation, and stakeholder management skills, with the ability to influence and collaborate effectively across business, technology, and data teams. • Proficient in Microsoft Excel, Access, Word, and PowerPoint. • Self-motivated, adaptable, and capable of operating effectively in a dynamic and fast-paced environment while managing multiple priorities. • Demonstrated ability to provide technical thought leadership, mentor and guide junior team members, and shape the strategic direction of Data and AI initiatives without direct people ma…