DSX Insights Generation Specialist

Roche•South San Francisco, CA

About The Position

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 DSX Insights Generation Specialist within the Analytical Data Science function of Roche Product Development Data Science (PDD) team serves as a Center of Excellence within the Analytical Data Science organization, focused on developing and enabling tools that drive data-driven decision-making across clinical programs. This group designs, tests, and promotes scalable analytics solutions such as dashboards, visualization packages, and reusable code modules that empower clinical and cross-functional teams to generate exploratory insights from complex datasets. While not directly responsible for operational programming delivery, the team collaborates closely with therapeutic area (TA) leads and study programmers to identify common challenges and embed insights-enabling capabilities into existing workflows. By bridging advanced programming techniques with user-centric design, the Insights Generator team helps elevate the organization’s analytics maturity and accelerates its ability to surface meaningful patterns and trends from clinical data.

Requirements

hold a Bachelor’s or Master’s degree in Statistics, Computer Science, Mathematics, Life Sciences, or a related field
have 2-4 years of experience in statistical programming, or an advanced degree with 0-2 years of equivalent work experience
have basic knowledge of a modern programming language (such as SAS or R) and visualization/review tools
have a basic understanding of statistical quality, endpoints, and QC processes
demonstrate strong logical thinking and attention to data integrity
bring effective communication and collaboration skills
demonstrate respect for cultural differences when interacting with colleagues in the global workplace
are fluent in English

Nice To Haves

Expertise in handling and analyzing different types of data (multi-modal) to identify and implement programming/analytical strategy
Familiarity with CDISC standards (SDTM, ADaM)
Demonstrated interest and critical thinking in data quality, reproducibility, and continuous learning
Ability to follow technical documentation and contribute to team processes
Experience working in cross-functional global study teams
Effective communication skills with the ability to translate complex statistical concepts for non-statistical audiences
Experience with multiple phases of drug development (early and/or late stage)
Excellent communication skills, including the ability to influence and translate complex data for non-technical stakeholders

Responsibilities

support the development, testing, and demonstration of standardized tools and code packages that enable exploratory data analyses and insights generation
leverage existing analytic libraries (e.g., R, Python, SAS macros) to build reusable components or visualizations under guidance from more senior colleagues
partner with study and portfolio programming teams to understand common insight needs and help refine DSX offerings to meet those needs
document tool functionality and provide basic user guidance for adoption across the programming community
participate in internal knowledge-sharing sessions to expand familiarity with modern analytics platforms and emerging programming approaches
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