Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection.
Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams.
Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences....
Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.
Conduct research and rapid prototyping of the most suitable AI algorithms and techniques based on best practices, particularly those involving LLMs to address technical and business requirements.
Write clean, well-tested, and well-documented code, contributing to efficient and maintainable system components....
Work as part of a cross-functional team of engineers, product managers and business analysts to build data science solutions that build customer engagement and help grow GoPay’s customer base and transactions.
Rapidly prototype data science solutions and be involved in product and feature discussions
Analyze large volume data and generate insights which will be actionable....
Lead advanced data science projects using sophisticated techniques to uncover insights, refine problem statements to solve challenges and deliver business value
Develop and implement AI/ML products with machine learning models, including Generative and Agentic AI frameworks, for specific business domains
Build web applications powered by machine learning and generative AI models, transitioning from proof-of-concept to production...
Data and Algorithms Innovation and R&D: Undertake development of new data models and algorithms to serve whole of government’s jobs-skills intelligence needs;
Jobs-Skills Product Management, Development and Delivery: Manage and enhance jobs-skills products, which includes UX/UI design and end-to-end product life cycle management;
Data Management and Operations: Centrally manage data quality, data models and data infrastructure to support internal and external users
Experiment with state-of-the-art multimodal models (VLMs, MLLMs, diffusion models, speech and audio models) and evaluate their applicability to government use cases and strategy
Design, build, and run evaluations and benchmarks for AI models on real-world Singapore government tasks — including constructing the underlying datasets, defining metrics and scoring, and standing behind results that inform agency and vendor decisions
Build functional prototypes and proof-of-concept solutions for agency engagements spanning smart city video analytics, document intelligence, generative media, and content authentication...
Terms of employment / engagement shall be subject to contract and local applicable laws
Participate in the design and development of algorithm strategies for user growth, including but not limited to user segmentation, intelligent recommendation, and incentive strategy optimization.
Build user lifecycle models (LTV prediction, churn warning, conversion prediction, etc.) based on user behavior data to drive precision operations and decision-making....
Implementing and benchmarking cutting-edge large language and multi-modal models and Agentic AI systems, analyzing their emergent patterns and system performance bottlenecks.
Lead and/or support end-to-end data science projects including data cleaning with large data sets(including processing, manipulation,analysis,modelling etc.)analyzing data trends,correlations and patterns,translating data into insights to drive business and operational decisions.
Act as an analytics translator, communicate complex data related requirements (from the business) to other parties (eg IT). Facilitate interactive design sessions with business user and use experimentation methods and design tests to optimize visualization experiences....
Prepare decision-ready data. Combine authorized primary research, market sources and enterprise inputs. Standardize units, time periods and definitions; resolve duplicates, missing values and outliers; retain source lineage and data-quality tests.
Build and compare models. Develop baselines and suitable forecasting, segmentation, scoring or optimization models. Document the business target, assumptions and limits; select complexity only where it improves validated performance or decision usefulness.
Validate and simulate. Use suitable time-based or held-out testing; check sampling bias, leakage and sensitivity. Quantify uncertainty where supportable; distinguish analyst scoring, statistical prediction and causal inference....
Analyse large-scale Visa transaction datasets to identify opportunities for portfolio growth, revenue enhancement, customer engagement, and profitability improvement.
Develop actionable insights across the cardholder lifecycle, including acquisition, activation, spend growth, retention, attrition prevention, and customer value management.
Conduct in-depth analyses of portfolio trends, customer behaviour, merchant spending patterns, and market opportunities at both market and group levels....
Set technical direction, standards and leading practices across data science, machine learning, GenAI and agentic AI
Remain hands-on in priority work through problem framing, exploratory analysis, methodological design, prototyping, and code or model review
Guide practitioners and partners, uphold technical quality, transfer knowledge and help shape the future regional data science and applied AI capability...
Research and assess next-generation technologies for machinery diagnostics and prognostics and data-driven modeling and optimization of complex systems.
Demonstrate advanced working knowledge and experience with machine learning algorithms and population-based meta-heuristic optimization methods.
Generate innovative ideas, establish new research directions, and shape and execute on technical projects....
Lead the delivery of end-to-end data science projects, including data acquisition, feature engineering, modeling, evaluation, and deployment.
Collaborate with stakeholders to understand business problems and translate them into analytical solutions.
Design and develop machine learning models, including generative models such as LLMs (e.g., GPT, Claude, LLaMA) for applications like text summarization, content generation, document intelligence, and chatbots....