Data Scientist
Posted 2hrs ago
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Job Description
Data Scientist building APIs, data products, machine-learning solutions and dashboards for Atos’s global digital transformation business. Supporting cloud deployments, MLOps and AI-enabled operational products.
Responsibilities:
- Develop scalable APIs and data services exposing trusted and governed data products
- Implement solutions supporting operational reporting and advanced analytics use cases
- Develop web applications and internal data products using modern front-end frameworks
- 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
- Identify opportunities for optimization, forecasting, automation and intelligent decision support
- Support deployment of machine learning models into production 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
- 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
- Develop and maintain automated unit, integration, contract and performance tests
- Support security-by-design principles including least-privilege access, secrets management, network security and encryption controls
Requirements:
- Good understanding of REST APIs and event-driven architectures
- Experience applying software engineering practices to the development of reliable, maintainable applications and data products
- 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
- 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
- Good understanding of CI/CD practices and DevSecOps principles
- Experience working with containerized applications and cloud-based environments
- 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
- 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

















