Graduate Data Scientist

• Develop and deploy predictive models using machine learning and statistical techniques.
• Clean, process, and analyse large datasets from diverse sources.
• Collaborate with software engineers and product teams to integrate data solutions.
• Create dashboards and visualizations to communicate insights.
• Support continuous improvement of data pipelines and model performance.

• A recent or upcoming graduate (2025/2026) with a degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Proficient in Python, R, or similar programming languages.
• Familiar with machine learning frameworks (e.g., scikit-learn, TensorFlow).
• Comfortable working with SQL and cloud-based data platforms.
• Strong analytical mindset and problem-solving skills.

Preferred (but not essential) Skills

• Experience with time-series analysis or anomaly detection.
• Knowledge of data visualization tools (e.g., Power BI, Tableau).
• Exposure to DevOps or MLOps practices.

• Competitive salary and benefits
• Structured development and mentoring
• Inclusive and diverse work culture
• Opportunities for global collaboration and career progression

NCR Atleos, headquartered in Atlanta, is a leader in expanding financial access. Our dedicated 20,000 employees optimize the branch, improve operational efficiency and maximize self-service availability for financial institutions and retailers across the globe. About NCR Atleos NCR Atleos is a global leader in financial self-service solutions, with over 20,000 employees worldwide. Our Dundee R&D centre is a hub for innovation, where data-driven insights power smarter services and better customer experiences across banking and retail sectors. Your Role As a Graduate Data Scientist, you'll join our Smart Services Engineering team, contributing to the development of intelligent systems that optimize ATM performance, predict failures, and enhance customer satisfaction. You'll work with large datasets, machine learning models, and advanced analytics to solve real-world problems.