Senior DSX Data Scientist
Role details
Job location
Tech stack
Job description
The 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 design, develop, and maintain robust statistical computing tools and platforms that support scalable, high-quality analytics across Product Development Data Sciences (PDD)
- You lead the development of reusable code modules, macro libraries, and workflow automation components that accelerate statistical programming and insight generation
- You serve as a key technical partner to statistical programmers, biostatisticians, and clinical scientists, translating scientific and operational needs into scalable, user-centered solutions
- You contribute to architectural decisions, codebase design patterns, and infrastructure improvements to enhance reproducibility, performance, and maintainability
- You lead or contribute to moderate-sized DSX projects, coordinating deliverables and ensuring alignment with broader development timelines and regulatory priorities
- You act as a functional mentor and technical resource to junior team members, fostering best practices in code development, testing, and documentation
- You collaborate cross-functionally to expand data visualization, workflow orchestration, and computing capabilities that enable faster, more flexible evidence generation
- You integrate feedback from internal users and stakeholders to iterate and improve DSX platforms, balancing innovation with reliability and compliance
Requirements
Do you have experience in Systems engineering?, Do you have a Master's degree?, * You hold a Master's degree or PhD in Computer Science, Data Science, Statistics, Bioinformatics, Engineering, or a related quantitative field
- You have experience in data science, statistical computing, or software engineering, preferably within a life sciences, healthcare, or regulated environment
- You have a proven ability to independently develop, optimize, and scale data science tools or platforms in support of clinical or scientific workflows
- You are proficient in programming languages such as R or Python, with hands-on experience in version control (e.g., Git), testing frameworks, and workflow orchestration tools
- You have a strong understanding of data pipelines, analytical workflows, and computational environments that support regulatory and exploratory analysis
- You have experience collaborating with cross-functional teams, translating user needs into scalable technical solutions, and iterating based on stakeholder feedback
- 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
Preferred:
- Experience designing and maintaining data science tools, packages, or platforms used by multiple teams across an organization
- Familiarity with enterprise-level statistical computing environments, containerized workflows (e.g., Docker, Kubernetes), or cloud-based infrastructure
- Demonstrated ability to contribute to or lead cross-functional initiatives involving data science, programming, and systems engineering
- Deep understanding of software development best practices (e.g., CI/CD, modularization, dependency management) in scientific programming contexts
- Experience implementing automation, reproducibility, or performance optimization within clinical or exploratory data workflows
- Ability to synthesize user requirements from scientists, programmers, and clinical teams into well-scoped, technical specifications
- Strong awareness of the evolving data science landscape in healthcare or pharma, including tools, standards, and innovation trends
- Previous contributions to internal knowledge-sharing, training, or code reuse efforts across departments or teams