Senior Data Analyst

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

At Roche, we are passionate about transforming patients’ lives, and we are bold in both decision and action - we believe that good business means a better world. That is why we come to work every single day. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all. We do this today to build a better tomorrow.

Roche is strongly committed to a diverse and inclusive workplace. We strive to build teams that represent a range of backgrounds, perspectives, and skills. Embracing diversity enables us to create a great place to work and to innovate for patients.

 Operations Near Patient Care (DOB) is a key pillar within Global Diagnostic Operations. Thanks to the systematic improvement of our cost structure, continuous optimizations, and efficiency enhancements, we are successfully positioning ourselves for growth in our environment

The Opportunity

Be part of our journey. As a Senior Data Analyst in our Near Patient Care manufacturing environment, you will develop and deliver data analytics solutions that help us understand, monitor and improve product and process performance across our portfolios, including CGM.

In this role, you will act as a Data Product Owner for selected analytics solutions and data products. You will translate business and process needs into clear analytical requirements, guide end-to-end delivery from problem framing to implementation and continuous improvement, and ensure that solutions are aligned with global data, platform and governance standards.

You will combine strong analytical expertise with a solid understanding of manufacturing processes, IT/OT systems and data engineering fundamentals. You will work hands-on where needed, while also providing technical guidance to colleagues and coordinating cross-functional teams to solve complex, high-impact problems.

Main tasks of the position

• End-to-End Data Product Ownership: Own and drive selected data products and analytics solutions with focus on CGM 2.0 (DOT) across their lifecycle, from business need, requirements and prioritization to development, testing, release, usage, continuous improvement and phase-out.

• Business Translation & Process Analysis: Work closely with manufacturing, quality, planning and digital stakeholders to understand process challenges, translate them into data and analytics requirements, and assess data needs based on operational value, feasibility, quality impact and scalability.

• Advanced Analysis & Monitoring: Independently perform complex analyses and establish effective process data monitoring to identify performance variation, prevent incidents and support the avoidance of quality deviations.

• Predictive System Modeling: Apply analytical thinking, data science methods and professional judgment to evaluate, select and implement approaches for predicting system and process performance.

• Data Engineering & Platform Alignment: Contribute hands-on to data preparation, data modelling, data quality checks and analytical implementation where required, and collaborate closely with data engineers and platform teams to ensure robust, scalable and maintainable solutions.

• Data Governance & Compliance: Contribute to data product governance and ensure that analytics solutions are developed in line with relevant data integrity, compliance, documentation and global platform requirements, including alignment with GO Digital 2.0 / Roche Diagnostics Data Mesh principles where applicable.

• Technical Leadership: Coordinate task distribution within cross-functional analytics work packages, provide expert guidance to colleagues and act as a best-practices resource for data analytics, data product delivery and analytical problem solving.

• Stakeholder & Performance Management: Proactively identify sources of product and process performance variation through data analysis, experiments and close collaboration with subject matter experts, ensuring that insights are