Data Scientist at Atos in Aberdeen, Scotland, GB

Atos is the Atos Group brand dedicated to AI-powered, secure, end-to-end digital services. Atos designs, develops, and operates critical digital environments that drive performance, resilience and sovereignty, helping public and private organizations worldwide retain control over their data and infrastructures, while meeting regulatory requirements.

With more than 54,000 employees serving over 4,500 clients across 54 countries, Atos helps modernize core IT systems, accelerate cloud and data transformation, strengthen cybersecurity, and deliver secure digital workplace environments to support its clients, its employees and society. Atos also provides consulting and advisory services through its Atos Amplify brand. A trusted partner in operating complex and mission-critical environments, Atos supports organizations across highly regulated and sovereign contexts.

About Atos Group

Atos Group is a global leader in digital transformation with c. 56,000 employees and annual revenue of c. €7.2 billion (at the go-forward perimeter), operating in 54 countries under two brands - Atos for services and Eviden for products and systems. European number one in cybersecurity and a leader in cloud, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is listed on Euronext Paris.

Key Responsibilities

• Develop scalable APIs and data services that expose trusted and governed data products and implement solutions that support both operational reporting and advanced analytics use cases.
• Develop web applications and internal data products using modern front-end frameworks such as React, Angular, Vue or similar.
• Develop and integrate REST APIs and, where appropriate, GraphQL APIs.
• Implement authentication and authorization mechanisms using enterprise identity providers.
• Collaborate with UX, Product and Business stakeholders to translate requirements into usable solutions.
• Test and operationalize predictive models and machine learning solutions.
• Collaborate with business stakeholders to identify opportunities for optimization, forecasting, automation and intelligent decision support.
• Support the deployment of machine learning models into production environments using MLOps practices.
• Work with structured, semi-structured and streaming data to generate actionable insights; Contribute to AI-enabled solutions including Generative AI, Agentic AI, NLP, forecasting and optimization where appropriate; Apply Infrastructure-as-Code principles to support repeatable cloud deployments.
• Build dashboards and visual analytics solutions using modern reporting and visualization tools; Translate complex analytical outputs into clear, business-focused insights.
• Work closely with Data Scientists, Analysts and operational stakeholders to maximize adoption of delivered solutions.
• Develop and maintain automated tests including unit, integration, contract and performance testing as appropriate.
• Understand and support security-by-design principles including least-privilege access, secrets management, network security and encryption controls.

Essential Skills & Experience

Software Engineering

• Good understanding of REST APIs and event-driven architectures.
• Experience applying software engineering practices to the development of reliable, maintainable applications and data products.

Data Engineering

• Strong practical data engineering experience.
• Understanding of partitioning, offset management, delivery guarantees and event-driven solution patterns.
• Experience building data pipelines and real-time or near-real-time processing solutions.
• Experience working with structured and semi-structured data.

Full Stack Development

• Experience developing user interfaces using a modern front-end framework such as React, Angular or Vue.
• Experience integrating front-end applications with APIs and data services.

Cloud & Platform Engineering

• Good understanding of CI/CD practices and DevSecOps principles.
• Experience working with containerized applications and cloud-based environments.

Data Science & Analytics

• Practical experience using Python for data science, automation or analytics.
• High-level appreciation of machine learning techniques, feature engineering and model deployment.
• Experience operationalizing analytical solutions within enterprise environments.
• Ability to collaborate effectively with Data Scientists and other analytical specialists to translate analytical approaches into production solutions.

Desirable Skills & Experience:

• Experience developing production-grade user experiences and data visualizations.
• Experience with MLOps platforms and model lifecycle management.
• Familiarity with optimization, forecasting and simulation techniques.
• Experience building or contributing to AI-enabled operational products.
• Exposure to Generative AI, Agentic AI or NLP solutions.
• Knowledge of data governance, metadata management and data quality frameworks.
• Some grounding in statistics and analytical problem-solving.
• Experience with Infrastructure-as-Code tools and approaches.

Benefits:

• Pension Scheme - contributions matched up to 10%
• Private medical cover
• Income Protection
• Life Assurance
• 25 days paid leave + National Holidays
• Flex benefits program

Diversity, Equity & Inclusion

At Atos, we want everyone to feel confident and supported throughout the recruitment process. As a proud signatory of the Armed Forces Covenant, Employers Domestic Abuse Covenant (EDAC) and Care Leaver Covenant, we welcome applications from individuals from all backgrounds and life experiences.

As a Disability Confident Leader, we guarantee an interview to disabled applicants who meet the minimum essential criteria for the role. If you require any reasonable adjustments during the recruitment process, please let us know and we will ensure the appropriate support is in place. Please contact the recruiter managing this vacancy or reach out to our dedicated mailbox: UK-Recruitment-Support@atos.net.

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