Data Scientist at ACI Worldwide in Co. Limerick

Job description

Powering the world’s payments ecosystem ACI powers the payments ecosystem – globally, and you power ACI. You’ll innovate, collaborate, and grow – in an energetic technology culture with decades of proven success. ACIers – in all roles and levels – are truly your colleagues and many are your friends. Our size and reach allow you to see the global impact of your work. You are visible, your talents are valued, and you are empowered to shape the future of payments. As a Data Scientist in Limerick, Ireland you will join a diverse, passionate team, dedicated to powering the world’s payments ecosystem! The purpose of the Data Scientist is: We are hiring a Data Scientist to join a modern, full-stack data science function at the heart of our fintech and payments business. This team owns the complete lifecycle of its models — from problem framing and data engineering through to model development, deployment and monitoring in production — with a direct mandate to strengthen how we detect and prevent financial crime across a global payments network. This is a genuinely exciting opportunity for a postgraduate-level data scientist to apply advanced statistical and machine learning methods to high-volume, real-world payments data, working alongside colleagues across multiple regions on problems that carry real financial and regulatory weight. You will work with a modern technology stack, including GPU-accelerated deep learning, and will be encouraged to bring research-driven thinking into a production engineering environment. A typical day at ACI for a Data Scientist is: Design and build statistical and machine learning models to detect, predict and prevent financial crime, fraud and anomalous payment behaviour, alongside broader AI applications across payments such as intelligent payment routing and foundation model development for payments intelligence. Contribute to the full data science lifecycle — data exploration, feature engineering, model development, validation, deployment and ongoing monitoring — within a full-stack data science team. Develop deep learning solutions using PyTorch, leveraging GPU/CUDA acceleration where appropriate to train and optimise models at scale. Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders, including risk, compliance and product teams. Collaborate across a global team of data scientists, engineers and subject-matter experts spanning multiple time zones and markets. Apply rigorous statistical methods to ensure models are robust, explainable and fit for a regulated financial environment. Contribute to the team’s engineering practices , including code quality, version control, testing and reproducibility of experiments. Stay current with advances in machine learning, deep learning and financial crime typologies, bringing new techniques into the team. Knowledge, Skills and Experience and Experience needed to succeed in this role: Bachelor’s degree in a relevant discipline such as Statistics, Mathematics, Computer Science, Data Science, Physics, Engineering or another quantitative field. This role is well suited to a postgraduate student or recent graduate looking to apply their research skills in an applied, industry setting Statistics – strong foundation in statistical theory and methods (hypothesis testing, probability, regression, experimental design) and their application to real-world data. Python – strong hands-on proficiency, including standard data science libraries (pandas, NumPy, scikit-learn). PyTorch – practical experience building and training neural network models. CUDA / GPU computing – experience accelerating model training using CUDA is favorable, though not essential. Communication – excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences. Machine learning fundamentals – solid understanding of supervised and unsupervised learning, and model evaluation