Data Scientist

As a Data Scientist, you will develop statistical, machine-learning and AI models for assigned Clinical Development questions with guidance from experienced colleagues. You will align analyses with study objectives, produce reproducible code and explain assumptions, findings and limitations. You will build pharmaceutical and clinical-data knowledge while using approved tools and methods with appropriate scientific and human review.

Responsibilities

• Apply statistical, stochastic and forecasting methods to questions involving study design, trial execution and monitoring.

• Apply standard ML and AI methods with guidance, comparing results with agreed baselines.

• Prepare permitted clinical datasets and document provenance, quality checks and evaluation splits.

• Develop reproducible R, Python and SQL code; record model, data and assigned prompt versions.

• Run agreed model tests and check AI outputs for errors, unsupported claims and limitations.

• Collaborate across regions with Data Science, Clinical Development, Programming, Statistics and data-platform partners.

• Test outputs with CfDA, GBS and GDO, seeking human review before clinical use.

• Understand end-user analytical needs and improve the usability of analytical outputs.

• Prepare reviewed findings, reproducible handoffs, user guidance and training materials.

Accountabilities

• Deliver reliable analyses and models that support decisions within assigned Clinical Development work.

• Protect sensitive data, use approved AI services and escalate unsafe or unreliable outputs.

• Contribute reusable analyses, evaluation cases, modeling components and documented workflows.

• Take ownership of agreed deliverables while escalating risks, assumptions and limitations.

• Maintain the quality, reproducibility and usability of code and outputs.

• Deliver validated analyses, models and documentation on time.

• Recommend modeling approaches and make code, testing and documentation decisions within agreed standards.

Basic Qualifications

• 5-9 years of experience over all

• Master’s degree; OR Bachelor’s degree and 2 years of related experience.

Preferred Qualifications

• Master’s degree in Mathematics, Statistics, Operations Research, Computer Science or another scientific or technical discipline.

• Internship or early-career experience in the pharmaceutical or high-tech industry.

• Strong capability in R and/or Python, with familiarity with SQL and data manipulation.

• Familiarity with reproducible workflows, version control, testing and documentation.

• Experience with statistical, simulation, forecasting or ML methods, with exposure to AI evaluation where relevant.

• Basic ML and generative AI literacy and the ability to learn approved tools with review.

• Working knowledge of statistical modeling, uncertainty, model validation and interpretation.

• Understanding of Clinical Development, or the ability to build this knowledge quickly.

• Ability to recognize AI errors, privacy risks and limits of use when handling permitted clinical data.

• Learning agility, quantitative reasoning, accountability and effective cross-functional communication.