Data Scientist

Role Overview

As a Data Scientist, you will join a diverse, passionate team dedicated to powering the world’s payments ecosystem. 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.

What You Will Do

A typical day at ACI for a Data Scientist is designing and building statistical and machine learning models to detect, predict, and prevent financial crime, fraud, and anomalous payment behavior. You will contribute to the full data science lifecycle, develop deep learning solutions using PyTorch, and translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders.

Why It Might Be a Fit

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.

Requirements

• Bachelor’s degree in a relevant discipline such as Statistics, Mathematics, Computer Science, Data Science, Physics, Engineering, or another quantitative field
• strong foundation in statistical theory and methods (hypothesis testing, probability, regression, experimental design)
• strong hands-on proficiency in Python, including standard data science libraries (pandas, NumPy, scikit-learn)
• practical experience building and training neural network models using PyTorch
• experience accelerating model training using CUDA is favorable, though not essential
• excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences
• solid understanding of supervised and unsupervised learning, and model evaluation and validation techniques
• comfort working with large, messy, real-world datasets, including SQL for data extraction and manipulation
• curious, rigorous approach to problem-solving, with sound commercial and risk judgement
• proven ability to work effectively in cross-functional, geographically distributed teams