At Data, Analytics & Research you are part of a global organization shaping the future of digital health at Roche. As a Senior Data Scientist and Data Lead (m/w/d), you will not only develop innovative data strategies but also act as a bridge between complex laboratory processes and cutting-edge digital products like navify Lab Operation. You are the driving force ensuring that the requirements of our partners are effectively translated into innovative solutions with high medical value.
In this role, you will lead the data strategy and oversee the comprehensive plan for how navify products collect, manage, and use data to enable scalability and future development.
Strategy & Collaboration: Align data initiatives with organizational strategy while fostering collaboration across the laboratory applications ecosystem.
Innovation: Generate and implement new ideas, including master data management, generative AI (e.g., nLO LabGPT), and “One Middleware” solutions.
Data Governance: Define and maintain internal data models and documentation while overseeing data privacy and compliance (PII, PHI).
Operations & Quality: Oversee data preparation (mocks, validation) and coordinate migration projects with a focus on high data quality.
Algorithm Development: Develop and refine algorithms (e.g., AON, refineR) to support product performance and scale advanced analytics solutions.
Stakeholder Support: Act as the key point of contact for data consumers (e.g., nMonitoring, nAnalytics) and deliver data-driven solutions for complex requirements.
You are a system thinker who navigates confidently through complex structures and the Roche ecosystem, promoting a culture of continuous learning.
Education: Master's degree in Data Science, Computer Science, Statistics, or a related quantitative field.
Experience: 8+ years of industrial experience in Data Science, preferably within healthcare, diagnostics, or highly regulated industries.
Domain Expertise: Deep knowledge of diagnostic testing and laboratory operations (pre-analytical to post-analytical phases) and familiarity with Laboratory Information Systems (LIS).
Technical Skills: Proven experience with R, Python, SQL, and big data/cloud technologies (AWS, Hadoop, Spark).
Mindset: Strong scientific acumen with the ability to translate complex datasets into evidence-based recommendations for clinical decision-making.
Agility: Experience working in an Agile environment (e.g., SAFe).
Communication: Excellent influencing abilities to collaborate effectively with cross-functional experts in global, matrixed environments.
We make it easy for you: Please only upload your current CV and the certificate of your highest degree.
We look forward to receiving your application!
Tagged as: Life Sciences
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