Data Science - Engagement Lead

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.