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

Let's build a healthier future, together.

By bringing together our unique strengths in medical, diagnostics, and technology, we take on the toughest health challenges, working with passion and purpose to prevent, stop, and cure diseases.

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’s Product Development (PD).

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 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 degree in Life Sciences, Computer Science, Epidemiology, Biostatistics, Public Health, Health Economics (HEOR), or a closely related quantitative field.
• You have a minimum of 3 years of experience working with structured data in a research or healthcare setting.
• You have solid working knowledge of R or Python, as well as SQL.
• You understand data dictionaries, mappings, or metadata tagging, as well as data systems used in clinical or operational settings.
• You demonstrate capacity for independent thinking, strategic agility, critical thinking, and the ability to make decisions based upon sound principles.
• 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:

• You hold a Master’s or PhD degree in Life Sciences, Computer Science, Epidemiology,
• Working knowledge of statistical methods and epidemiological concepts used in observational healthcare research (e.g., cohort identification, censoring, time-to-event concepts).
• Prior experience in immunology or infectious disease therapeutic areas.
• Familiarity with clinical terminologies and coding systems (e.g., ICD, SNOMED CT, RxNorm, CPT, HCPCS), 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).

Relocation benefits aren’t available for this position. 

The expected salary range for this position based on the primary location of Mississauga is 89,256.00 and 117,148.50 of hiring range. Actual pay will be determined based on experience, qualifications, and other job-related factors as determined by the company.

We use artificial intelligence to screen, assess or select applicants for this role.

This posting is for an existing vacancy at Hoffmann-La Roche Ltd.

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.