RocheD2P Data & Analytics Senior Data Scientist - RDT ERP
Roche is hiring a D2P Data & Analytics Senior Data Scientist - RDT ERP in Madrid, Spain. Level rates it ; you can apply on Level.
AI in this role
Lead development of AI and GenAI applications, building end-to-end solutions with LLMs, RAG pipelines, and agentic workflows.
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
D2P Data & Analytics Senior Data Scientist - RDT ERP is responsible for leading, developing, and implementing data-driven AI and GenAI solutions to complex business problems. This role involves independently identifying analytical opportunities, conducting in-depth data exploration and analysis, and building, testing, and deploying predictive models using various machine learning techniques. You will own projects from inception to deployment, leveraging strong programming, statistical modeling, and data visualization skills, while clearly communicating findings to both technical and non-technical stakeholders.
Description of the area
The Demand to Pay (D2P) Data & Analytics area is responsible for driving the end-to-end Procurement, Accounts Payable and Travel & Expense Management Data & AI strategies by translating Functional strategies into measurable business outcomes. We’re looking for a hands-on Full-Stack AI Developer (Generalist) to join a small, fast-moving team. This role is ideal for someone who enjoys building end-to-end products, thrives in ambiguity, and is excited about applying AI in practical, user-facing applications.
This role seeks a broad skillset, strong foundational knowledge, and tech stack flexibility over deep specialization. You will support Roche's Data & AI strategies by working with global platforms.
This position involves collaboration with key stakeholders, including Global Procurement, Diagnostics Direct Procurement, and RSS Operations.
Job Responsibilities
- Design, build, and ship AI-powered applications from concept to production
- Develop backend services and APIs using Python
- Build responsive frontend interfaces using JavaScript / TypeScript
- Integrate LLMs into products for real-world use cases
- Build and improve RAG pipelines, prompt workflows, and agentic AI systems
- Work with modern AI coding tools to accelerate development and delivery
- Collaborate closely with product and business stakeholders in a fast-paced environment
- Take ownership of features across architecture, implementation, testing, and deployment
Qualifications
Education / Experience
- A bachelor's degree in Computer Science, Software Engineering, or a related field preferred
- Equivalent practical experience is fully acceptable
- Demonstrated experience in independently identifying analytical opportunities, conducting in-depth data exploration, and owning projects from inception to deployment.
- Proven track record of driving medium-sized projects that influence business decisions and align with strategic objectives.
- A strong portfolio / GitHub profile with personal projects is highly valued
Technical Skills
- Strong experience in Python backend development
- Solid experience with JavaScript / TypeScript frontend development
- Comfortable working across the full stack and shipping complete features
- Snowflake CORTEX AI or Dataiku (Optional)
AI / GenAI Experience
- Practical experience building AI-powered applications
- Strong understanding of:
- Prompt engineering
- RAG (Retrieval-Augmented Generation) pipelines
- LLM integrations
- AI agents / agentic workflows
- Experience with frameworks/tools such as:
- LangChain
- LangGraph
- or similar AI orchestration frameworks
AI Coding Tools
You should actively use AI-assisted coding tools as part of your daily workflow. This is a key requirement and will significantly amplify all other capabilities.
For Examples:
- Claude Code
- OpenAI Codex
- Cursor
- GitHub Copilot
Additional Qualifications
- Exceptional communication skills, with the ability to present complex findings clearly to various stakeholders, including non-technical audiences.
- Strong collaborative capabilities to effectively engage with broader business units to understand and meet data needs.
- Product-minded and pragmatic, comfortable switching between frontend, backend, and AI workflows.
- Fast learner with strong fundamentals, Self-driven and proactive, and Enjoys working in teams with high ownership
#RDT2026
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an Equal Opportunity Employer.
How we rate this
D2P Data & Analytics Senior Data Scientist - RDT ERP at Roche rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How have you integrated a large language model into a production application?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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