Data & Quantitative Sciences Statistical Programming Intern

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Collaborate with a project supervisor and subject-matter experts to comprehend a statistical programming, clinical data, automation, or technology-related business challenge, translating it into project goals and deliverables.

• Create, develop, test, and document a prototype, analytical workflow, automation solution, or reusable programming methodology.

• Utilize SAS, R, and/or Python for data processing, analysis, automation, validation, or clinical programming applications.

• Investigate automation, generative AI, metadata-driven strategies, or open-source technologies to enhance programming efficiency and quality.

• Work with structured data and metadata and, when relevant, gain experience with CDISC standards such as SDTM, ADaM, and Define-XML.

• Conduct structured testing and validation to assess solution accuracy, consistency, reliability, and limitations.

• Compare outcomes against existing processes or recognized methodologies, documenting discrepancies, assumptions, limitations, and areas needing human review.

• Partner with statistical programmers and cross-functional stakeholders to gather requirements, solicit feedback, and refine solutions.

• Prepare technical documentation and summarize project insights, lessons learned, and recommendations.

• Present the final project and key findings to Statistical Programming colleagues and other stakeholders at the end of the internship.

⛳️ Requirements

• Currently enrolled in a Master’s degree program in Statistics, Biostatistics, Data Science, Computer Science, Software Engineering, Mathematics, or a closely related quantitative field.

• Must continue in the Master’s degree program after the internship concludes.

• Experience in programming with at least one of SAS, R, or Python.

• Foundational understanding of data manipulation, analytical programming, statistical computing, software development, or related quantitative methods.

• Proven ability to learn new programming languages, tools, and technical concepts.

• Strong analytical and problem-solving capabilities with a keen attention to detail.

• Excellent written and verbal communication skills.

• Preferred: experience with two or more of SAS, R, and Python.

• Preferred: familiarity with Git/GitHub, Visual Studio Code, automated testing, or reproducible programming workflows.

• Preferred: knowledge of clinical trial data or healthcare, life sciences, or other regulated data.

• Preferred: familiarity with CDISC standards, especially SDTM, ADaM, Define-XML, or clinical trial metadata.

• Preferred: experience or coursework related to generative AI, large language models, automation, software testing, APIs, XML/JSON, or data visualization.

• Preferred: interest in applying emerging technology to clinical development and statistical programming processes.

🏝️ Benefits

• Opportunities for growth.

• Supportive environment.

• Inclusion, wellbeing, flexibility, and comprehensive benefits.

• Interns and co-op participants may be eligible for limited benefits depending on program structure, work location, and local requirements.