DSX Data Scientist (On Site, Clinical Trial Data, CSRs)

Genentech•Daly City, CA

73d•Onsite

About The Position

DSX Data Scientist (On Site, Clinical Trial Data, CSRs) Department Summary This role is in Analytical Data Science, a core function within Product Development Data Sciences (PDD) that provides strategic leadership and scientific rigor across Development at Roche. PDD Analytical Data Science teams are mobilized across the portfolio to generate data-driven insights, identify opportunities for scale, and implement impactful solutions. PDD Analytical Data Science is recognized as a leading hub for top industry talent, operating as an agile workforce to deliver regulatory commitments across the portfolio. We identify, influence, and adopt industry-leading digital and automation solutions, develop analytical approaches to support exploratory analyses, and align statistical programming practices across both early- and late-stage clinical development. The Opportunity The Data Scientist in the Data Science Acceleration (DSX) team is responsible for developing scalable tools, environments, and workflows that enable efficient, high-quality statistical computing across Product Development Data Sciences (PDD). This role focuses on creating and maintaining next-generation capabilities that support automation of programming workflows, generation of reusable coding macros, and advanced data visualization. Working closely with statistical programmers, biostatisticians, and clinical scientists, the Data Scientist translates scientific and operational needs into robust, modular, and user-friendly solutions that streamline evidence generation and support faster, more reliable decision-making across the development pipeline. You contribute to the design, development, and maintenance of statistical computing environments and tools that enable efficient analysis of clinical and operational data. You develop and implement reusable code libraries, macros, and automation pipelines to support programming workflows across PDD. You collaborate with statisticians, programmers, and data scientists to translate user needs into robust, scalable technical solutions. You support exploratory analytics and data visualization capabilities that enhance insight generation and decision-making across development programs. You apply software engineering best practices, including version control, testing, and documentation, to ensure high-quality, reproducible code. You participate in the continuous improvement of DSX tools and infrastructure, incorporating feedback and emerging technologies. You support regular review of opportunities to simplify and innovate, and collaborate with experts in PDD and beyond to accelerate and deliver patient benefits faster. You work under general supervision and apply independent judgment to interpret guidance, prioritize responsibilities, and make decisions in situations that require contextual understanding. You apply judgment to address moderately complex statistical or data issues, balancing scientific rigor with appropriate flexibility, and seek guidance when facing novel or ambiguous situations. You adhere to functional standards by participating in peer review and mentoring relationships to uphold quality and build methodological and programming expertise.

Requirements

You hold a Master’s degree or PhD in Computer Science, Data Science, Statistics, Bioinformatics, Engineering, or a related quantitative discipline.
You have 2+ years of hands-on experience in data science, statistical computing, software engineering, or a related field, preferably in a life sciences or healthcare setting (internship and academic experience will be considered).
You are proficient in programming languages commonly used in statistical computing (e.g., R, Python) and are familiar with development tools such as Git, Docker, or workflow automation tools.
You understand clinical trial data structures, statistical analysis concepts, or biomedical data (e.g., omics, real-world data, operational data).
You demonstrate ability to build, test, and maintain reproducible, well-documented code.
You demonstrate capacity for independent thinking and ability to make decisions based upon sound principles.
You bring 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 have 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.

Nice To Haves

Experience working with diverse data modalities (e.g., clinical, operational, real-world, omics) and applying analytical strategies to uncover patterns or insights.
Familiarity with statistical computing workflows in regulated environments, including clinical trial data structures and lifecycle.
Demonstrated interest in data engineering best practices (e.g., reproducibility, code modularity, testability, documentation).
Ability to follow and contribute to collaborative development processes, including code reviews, version control, and continuous integration.
Experience contributing to the development or extension of statistical platforms, macro libraries, or reusable toolkits.
Strong communication and collaboration skills, with the ability to translate user needs into technical requirements and explain complex solutions in accessible terms.
Exposure to automation, workflow orchestration tools (e.g., Airflow, Nextflow), or containerization (e.g., Docker, Kubernetes) is a plus.
Experience working in multi-disciplinary or matrixed R&D teams, preferably within a global pharmaceutical or biotech organization.

Responsibilities

contribute to the design, development, and maintenance of statistical computing environments and tools that enable efficient analysis of clinical and operational data
develop and implement reusable code libraries, macros, and automation pipelines to support programming workflows across PDD
collaborate with statisticians, programmers, and data scientists to translate user needs into robust, scalable technical solutions
support exploratory analytics and data visualization capabilities that enhance insight generation and decision-making across development programs
apply software engineering best practices, including version control, testing, and documentation, to ensure high-quality, reproducible code
participate in the continuous improvement of DSX tools and infrastructure, incorporating feedback and emerging technologies
support regular review of opportunities to simplify and innovate, and collaborate with experts in PDD and beyond to accelerate and deliver patient benefits faster
work under general supervision and apply independent judgment to interpret guidance, prioritize responsibilities, and make decisions in situations that require contextual understanding
apply judgment to address moderately complex statistical or data issues, balancing scientific rigor with appropriate flexibility, and seek guidance when facing novel or ambiguous situations
adhere to functional standards by participating in peer review and mentoring relationships to uphold quality and build methodological and programming expertise