Data Science - Engagement Lead

Roche is hiring a Data Science - Engagement Lead in San Jose, Costa Rica. Level rates it ; you can apply on Roche.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include LangChain, CrewAI and AutoGen.
Level classifies it as a lead role.
Level lists 1,200+ other open roles at Roche.

AI in this role

Data Science Engagement Lead architecting enterprise AI solutions, mentoring data science talent, and driving predictive and generative AI initiatives.

LangChainCrewAIAutoGenMLflowSageMakerPythonMLOps

ragfine-tuningml-opsmachine-learningartificial-intelligencegenerative-aicausal-inferencetechnical-leadership

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

As a Data Science - Engagement Lead, you will join the Global Analytics and Technology Center of Excellence (GATE) within Roche Services & Solutions (RSS) in San José, Costa Rica. In this high-impact, technical leadership role, you will architect advanced enterprise AI solutions, mentor data science talent, and serve as a strategic consultant across global business divisions (Commercial, R&D, Diagnostics). Operating in an agile environment, you will drive predictive, causal, and generative AI initiatives while shaping GATE-level product strategy, talent enablement, and cross-center innovation.

The Opportunity

Technical Leadership & Mentorship: Lead and mentor Senior Data Scientists across Predictive AI and Causal & Experimentation AI sub-teams, fostering modular coding standards, MLOps best practices, and agile delivery.
Strategic Business Consulting: Act as a trusted AI consultant to global executive stakeholders, translating complex healthcare and business challenges into actionable Data Science and AI strategies.
GATE Strategy & Product Roadmap: Drive GATE-wide center initiatives, shaping AI product development strategy, talent enablement programs, and standard methodologies across the ecosystem.
Rapid Prototyping & ROI: Design and build Proofs of Concept (POCs), prototypes, and business cases to demonstrate tangible value and secure executive buy-in.
Advanced AI Architecture: Architect robust predictive models, causal inference frameworks (A/B testing, quasi-experiments), and Enterprise Generative AI solutions (RAG, fine-tuning, Agentic AI workflows).
End-to-End MLOps & Delivery: Partner with Data Engineering and MLOps teams to design, operationalize, and maintain scalable ML/AI pipelines, ensuring automated deployment and monitoring.
Agile Collaboration: Collaborate across global cross-functional teams, facilitating reviews, demos, and retrospectives to continuously enhance solution delivery.

Who You Are

Bachelor’s or Master’s degree in Data Science, Statistics, AI/ML, Computer Science, Quantitative Analytics, or a related field. Professional certifications in Data Science, Cloud AI, or GenAI are advantageous.
12+ years of overall experience in Data Science/AI, including 5+ years leading AI product lifecycles and mentoring data science teams.
Proven track record in predictive modeling, causal inference, LLMs, RAG, and Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI).
Hands-on experience with Python, SQL, modern pipeline tools (dbt, PySpark), MLOps platforms (MLflow, Kubeflow, AWS SageMaker), containerization (Docker, Kubernetes), and AWS.
Exceptional communication and consulting skills with a demonstrated ability to present business cases to executive leadership (pharmaceutical or healthcare domain experience is a plus).
Must be currently based in Costa Rica or hold valid work authorization for San José.

No relocation benefits are offered for this position.

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

Data Science - Engagement Lead at Roche rates 90 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.

Classification

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. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Science - Engagement Lead is an open job at Roche.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in San Jose, Costa Rica.
The job was posted on September 18, 2026.
Seniority: lead.
Applications are handled by Roche. Apply on Roche

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGFine-tuningML OpsMachine learningArtificial IntelligenceGenerative AICausal InferenceTechnical Leadership

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where artificial intelligence was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, Fine-tuning, ML Ops, Machine learning, and Artificial Intelligence. 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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