Data Strategy & Analytics Specialist - Basel - Solid Oncology

Chez Roche, vous pouvez être vous-même et être apprécié pour les qualités uniques que vous apportez. Notre culture encourage l'expression personnelle, le dialogue ouvert et les connexions authentiques, où vous êtes valorisé, accepté et respecté pour ce que vous êtes, vous permettant de prospérer tant personnellement que professionnellement. Voici comment nous visons à prévenir, arrêter et guérir les maladies et à garantir à chacun l'accès aux soins de santé aujourd'hui et pour les générations à venir. Rejoignez Roche, où chaque voix compte. La position A healthier future.

It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. This role is based in the Real-World & Clinical Data Strategy (RWCDS) team which drives data excellence and analytics to power enhanced decision-making and evidence-generation within Roche Product Development.

We develop and implement data strategies that unlock the value of clinical, operational, and real-world data to accelerate evidence generation, decision-making, and innovation across PD and beyond. By embedding FAIR principles, advancing data governance, and enabling data productization, RWCDS ensures that data is not only findable and usable, but also a driver of scientific rigor, regulatory readiness, and AI-powered transformation.

Through deep partnerships with internal functions and external collaborators, we shape a future-ready data ecosystem that supports personalized healthcare and efficient drug development. The Opportunity: The Data Strategy & Analytics Specialist contributes to the design and execution of data strategies and analyses that enable decision-making and insight generation across a therapeutic area or molecule portfolio. Working under the Data Strategy & Analytics

• Lead, you will partner with cross-functional teams—translating scientific protocols into robust analytical code, cohort extractions, and reproducible pipelines using multi-modal real-world data and clinical assets. You will also contribute to the translation of scientific and business needs into analytical frameworks and data-driven solutions. This role demands strong core data science skills, analytical execution, and a growth mindset to continuously elevate team standards.
• You execute data transformations, cohort extractions, and descriptive/observational analyses leveraging real-world (EHR, Claims, etc.), clinical trial data for secondary use, and operational multi-modal domains
• You translate analytical or study requirements into cohort definitions, derived variables, and analysis-ready datasets.
• You follow state-of-the-art coding best practices, version control, unit testing, and structured QC routines to guarantee fully reproducible analytical pipelines.
• You summarize and visualize exploratory analytical outputs, cohort characteristics, and study results to communicate findings effectively to project teams.
• You partner seamlessly with RWD Scientists and cross-functional study leads during study framing and protocol development, providing active feedback on data availability, feasibility, methodology, and execution.
• You actively contribute well-documented code snippets, analytical templates, and learnings to the internal team repository.
• You assist in identifying fit-for-purpose real-world data (RWD) sources, performing data quality evaluations, terminology mappings, and schema transformations for secondary data use.
• You partner with study teams and central data engineering functions to gather analysis requirements, specify derived variables (e.g., ADaM, ARDs), and shape clinical trial data marts for secondary use.
• You collaborate with central data engineering and governance teams to guide multi-modal data integration, applying common data models (OMOP, CDISC) and structured mappings across clinical trial and real-world assets.
• You collaborate with internal partners to analyze data structures, document data lineage, and maintain structured, compliant, and accessible data assets to support long-term data strategy and reusability.
• You safely leverage modern AI coding tools and LLM assistants (e.g., Claude Code, Copilot) to accelerate scripting, query building, and data extraction while maintaining scientific rigor and code quality. Who you are:
• You hold a Bachelor’s or Master’s degree in Life Sciences, Computer Science, Epidemiology, Biostatistics, Public Health, Health Economics (HEOR), or a closely related quantitative field
• You have 2+ years of experience working with structured data in a research or healthcare setting (please note: internships and any study-related placements/practical experience are excluded).
• You have solid working knowledge of R or Python, as well as SQL
• You understand data dictionaries, mappings, or metadata tagging
• You are familiar with data systems used in clinical or operational settings
• You demonstrate capacity for independent thinking and ability to make decisions based upon sound principles
• You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond the technical domain
• You demonstrate respect for cultural differences when interacting with colleagues in the global workplace
• You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language Preferred

- Working knowledge of descriptive statistical methods and epidemiological concepts used in observational healthcare research (e.g., cohort identification, censoring, time-to-event concepts). - Prior experience in Oncology. - Familiarity with clinical terminologies and coding systems, including ICD, SNOMED CT, RxNorm, CPT, and HCPCS. - Exposure to real-world data common data models (e.g., OMOP CDM) or CDISC standards (SDTM, ADaM). - Familiarity with software engineering best practices (Git, unit testing) and AI-assisted coding tools (e.g., Claude Code, GitHub Copilot).

This position is based in Basel and relocation assistance is not available. Ready to make your next big move? If this sounds like the perfect fit for you, we’d love to chat! Send us your CV and a cover letter telling us why you’re excited about this role, and apply today! #PDDT #PDDBasel Qui nous sommes Un avenir plus sain nous pousse à innover. Ensemble, plus de 100 000 employés à travers le monde sont dédiés à faire progresser la science et à garantir à chacun l'accès aux soins de santé aujourd'hui et pour les générations à venir.

Nos efforts aboutissent à plus de 26 millions de personnes traitées avec nos médicaments et plus de 30 milliards de tests réalisés avec nos produits de Diagnostique. Nous nous encourageons mutuellement à explorer de nouvelles possibilités, à favoriser la créativité et à conserver nos grandes ambitions, afin de fournir des solutions de santé qui changent des vies et ont un impact mondial. Construisons ensemble un avenir plus sain. Roche est un employeur offrant l'équité en matière d'emploi.

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