Data Scientist – Pharma R&D (Patient Safety & Medical Affairs) Full-time NEW

Data Scientist – Pharma R&D (Patient Safety & Medical Affairs)

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 Patient Safety & Medical Affairs Data Scientist executes complex, end-to-end data science projects by bridging medical strategy with cutting-edge technical execution to drive significant business impact and enable informed decision-making for senior leaders. In this high-impact role, you will lead the charge in establishing an “AI-first” culture, prototyping and productionizing sophisticated machine learning models and causal inference methods that transform medical inquiries into automated, “decision-grade” insights. You will champion the “Talk to the Data” initiative by architecting the semantic and logical frameworks that allow stakeholders to leverage GenAI for natural language discovery, while simultaneously driving data interoperability and end-to-end integration across the Medical Affairs landscape to redefine departmental efficiency on an enterprise scale.

Within the Pharma Organisation Medical Affairs serves as the bridge between clinical development and the commercialization of medicines driving product differentiation and adoption through integrated evidence planning & generation. As a Data Scientist for Medical Affairs Evidence Planning and Generation, you will design, build, and scale data and AI-enabled capabilities that accelerate Integrated Evidence Planning (IEP) and evidence generation across Roche Medical Affairs.

Job Responsibilities

• Strategy & “AI-First” Leadership: Partner with senior leaders to develop data and technology strategies that enable informed decision-making across Medical Affairs. Act as a primary advocate for an “AI-first” mindset, spearheading the “Talk to the Data” initiative to improve departmental efficiencies and modernize how the organization interacts with medical information.
• Evidence planning enablement: Translate evidence questions from Medical Affairs stakeholders into analytics-ready technical requirements (cohort definitions, study designs, feasibility) for RWE and NIS programs. Build repeatable, traceable workflows connecting evidence needs to data assets and analytic outputs to enable “decision-grade” evidence planning.
• GenAI & Semantic Framework Architecture: Design and implement the semantic and logical frameworks required to power natural language discovery. Enable stakeholders to leverage Generative AI to query complex evidence datasets intuitively, transforming how medical questions – ranging from PICO-based inquiries to subgroup analyses – are translated into technical requirements and actionable insights.
• Insights Management and Evidence Generation: Drive the end-to-end integration of the Medical Affairs data landscape by ensuring seamless interoperability between disparate systems and Real-World Data (RWD) sources. Architect robust pipelines and data standards that connect medical insights (e.g., patient and HCP perspectives) or registries and global data networks, creating unified data models that accelerate decision making and endpoint derivation and reduce time-to-analysis.
• AI/ML and analytics applications (with experimentation): Prototype and productionize analytics and ML solutions, including predictive models, causal inference methods, and decision automation, to support evidence generation. Contribute to imaging/digital pathology use cases and apply strong engineering practices (documentation, reproducibility, monitoring) to ensure robust model development and deployment in a pharma environment.
• Complexity / (Product Size): Manages enterprise-level datasets and builds intricate, sophisticated predictive models. Designs and implements comprehensive data science frameworks and sets organizational best practices.

Qualifications

Education / Experience

• Bachelor's or advanced degree in a quantitative field (e.g., computer science, engineering, statistics, applied math, data science, bioinformatics, or similar), or equivalent practical experience.
• Extensive experience leading complex data science projects from end-to-end and driving significant business impact.
• Proven track record of working closely with senior leadership to inform and influence high-level strategic business decisions.
• Demonstrated experience in designing and implementing enterprise-wide data science frameworks and best practices.

Technical Skills

• Deep expertise and expert-level proficiency in multiple programming languages (e.g., Python, SQL, R), sophisticated data analysis
• In-depth understanding and hands-on capability with state-of-the-art machine learning, AI techniques incl. GenAI frameworks, and experimental design.
• Strong background in data architecture, with the ability to manage enterprise-level datasets, optimize model performance, and ensure successful deployment and monitoring in production.

Additional Qualifications

• Strong leadership and mentorship capabilities, with a proven ability to oversee multiple projects simultaneously and guide junior to mid-level data scientists.
• Strategic mindset with the ability to shape the team's technical roadmap and the broader data science vision of the organization.
• Expertise in medical data types (e.g., pharmacovigilance reports, EHRs, RWD, clinical evidence and imaging), RWD data and interoperability standards (e.g. OMOP, ICD10), medical imaging/digital pathology workflows, medical/life sciences data regulation and compliance (e.g., HIPAA/GDPR context)
• Experience contributing to scientific/academic collaborations (methods co-development, multi-site feasibility, publication-grade rigor) (preferred)

What you get:

• Salary range 19,000 – 35,400 PLN gross based on the employment contract.
• Annual bonus payment based on your performance (target 20%).
• Dedicated training budget (training, certifications, conferences, diversified career paths etc.).
• Recharge Fridays (2 Fridays off per quarter available).
• Take time Program (up to 3 months of leave to use for any purpose).
• Vacation subsidy available.
• Flex Location (possibility to perform our work from different places in the world for a certain period of time).
• Take Time for Charity (additional paid leave of maximum 2 weeks to engage in the charity action of your choice).
• Private healthcare (LuxMed packages), group life insurance (UNUM) and Multisport.
• Stock share purchase additions.
• Yearly sales of company laptops and cars and many more!

Apply directly and join us in shaping the future of healthcare.