Data Business Analyst & Adoption Lead

Orange

6d • Hybrid

About The Position

If ‘AI platforms at scale’ sounds like the right place to grow your skills, we should definitely talk.
You contribute to the design, deployment and operation of AI platforms, ensuring reliability, scalability and security in production environments.
You work closely with data scientists, data engineers and infrastructure teams to industrialize AI use cases on cloud and hybrid platforms.
You implement and maintain the tooling and pipelines required for model training, evaluation, deployment and monitoring (MLOps).
You help automate and standardize platform services (templates, CI/CD, infrastructure as code) to accelerate delivery while keeping quality high.
You participate in incident analysis and continuous improvement of the AI platform, contributing to a strong reliability and performance culture.
This position offers you the opportunity to deepen your expertise in AI platform engineering, from build to run. You will strengthen your skills in cloud environments, containerization, MLOps and observability, while gaining experience on real-life, large-scale AI use cases. You will also develop your ability to collaborate with cross-functional teams, translate data science needs into robust platform services, and grow your autonomy and technical leadership in an international and agile environment.

Requirements

• Between 3 and 5 years of professional experience in a relevant technical role (for example: platform engineer, DevOps engineer, data/ML engineer, software engineer)
• At least a Bachelor’s or Master’s degree (or equivalent) in computer science, engineering or a related field.
• Good knowledge of cloud environments (AWS, Azure or GCP) and their managed services for data and AI.
• Solid experience with containers and orchestration (Docker, Kubernetes) in production contexts.
• Hands-on experience with CI/CD and DevOps practices (Git, pipelines, infrastructure as code such as Terraform/Ansible, monitoring/logging tools).
• Familiarity with AI and ML concepts and tools (for example Python-based ML stacks, model serving frameworks, MLOps tools) and a strong motivation to grow further in this area.
• Understanding of security, reliability and performance considerations for production platforms.
• Team player with good communication skills
• Show rigor, curiosity and a strong willingness to learn
• Comfortable taking ownership of problems, proposing solutions and iterating in an agile way.
• Mindset combines pragmatism and a desire for quality

Responsibilities

• Contribute to the design, deployment and operation of AI platforms
• Work closely with data scientists, data engineers and infrastructure teams to industrialize AI use cases on cloud and hybrid platforms
• Implement and maintain the tooling and pipelines required for model training, evaluation, deployment and monitoring (MLOps)
• Help automate and standardize platform services (templates, CI/CD, infrastructure as code) to accelerate delivery while keeping quality high
• Participate in incident analysis and continuous improvement of the AI platform

Benefits

• Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
• Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
• Professional Development: training programs and upskilling/re-skilling opportunities.
• Career Growth: Internal growth and mobility opportunities within Orange.
• Caring and Daring Culture: Health and well-being programs and benefits, diversity & inclusion initiatives, CSR and employee connect events.
• Reward Programs: Employee Referral Program, Change Maker Awards.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees