2 of 2 Permanent Data Science Jobs in Angus

Smart Services Engineering - Graduate Data Science/Analyst page is loaded Smart Services Engineering - Graduate Data Science/Analyst Apply locations DUNDEE, GBR time type Full time posted on Posted 9 Days Ago job requisition id R About NCR Atleos NCR Atleos, headquartered in Atlanta, is a leader in expanding financial access. Our dedicated … employees optimize the branch, improve operational efficiency, and maximize self-service availability for financial institutions and retailers across the globe. Title: Smart Services Engineering - Graduate Data Science Engineer Grade: 9 Location: Dundee, UK Smart Services Engineering - Graduate Data Science Engineer We are looking for Graduates! Our University Hiring vision is to hire and nurture talented graduates … Engineering team where you will be offered mentorship and resources to deliver company value and build your career. Who you are We seek STEM graduates with a background in Data Science or related fields who are passionate about data manipulation and analysis. You will work on challenging global projects requiring smart solutions, supported by experienced team members. More ❯

s tech. The new MLOps team will be responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data science and R&D teams, this team will ensure that ML models transition smoothly from development to production, maintaining high availability, scalability, and performance. Key responsibilities include: Managing … and optimising existing ML model deployments to ensure reliability and efficiency. Continuously improving the architecture, processes, and tools used for model deployment, monitoring, and lifecycle management. Collaborating closely with data scientists to understand and implement model requirements. Partnering with R&D teams to align technical strategies and integrate ML solutions into broader systems. Implementing robust CI/CD pipelines … high-performance, scalable backend systems and APIs. Knowledge of systems programming concepts: memory management, concurrency, performance optimization. Familiarity with ML system architecture and computational requirements (model serving, training infrastructure, data processing pipelines). Experience with cloud platforms (AWS preferred) and distributed systems. Proficiency with containerization (Docker) and orchestration tools (Kubernetes). Strong experience with version control systems (Git) and More ❯