Senior Data Scientist

Position Summary

Bristol Myers Squibb is seeking a Senior Data Scientist to design and deploy AI-powered applications that optimize workflows, automate processes, and enhance data validation and visualization. The role involves developing scalable web applications, building AI-powered interactive visualization platforms, and maintaining a strong understanding of data science workflows.

Key Responsibilities

• Design and implement scalable web applications to support data science workflows, including tools for data ingestion, parsing, examination, and cleaning of clinical datasets.
• Develop AI-powered interactive visualization platforms to investigate complex datasets, identify patterns and anomalies, and communicate insights clearly to both technical and non-technical stakeholders.
• Maintain LLM-powered applications and intelligent agents that assist in data processing, document handling, and decision support.
• Evaluate and champion emerging AI technologies and frameworks, proposing and implementing relevant advancements to enhance team capabilities and tooling.
• Collaborate with cross-functional teams to translate operational and scientific needs into robust, intelligent software solutions.
• Support preparation of analysis-ready datasets for NONMEM or other modeling tools using SAS, R, or other programming languages, applying foundational knowledge of PK/PD and clinical data concepts.
• Aid in the preparation of submission packages (datasets, TLFs, PMx report data sections) and perform quality control to ensure data accuracy and consistency across studies.

Qualifications & Experience

• Master's degree (or Bachelor's with significant experience) in Engineering, Computer Science, Information Technology, Mathematics, Statistics, or a related quantitative field.
• 2+ years of hands-on software development experience.
• Proficiency in Python and JavaScript/TypeScript.
• Full-stack development experience with modern web technologies (e.g., React, Angular, FastAPI, Flask, Node.js).
• Ability to implement sophisticated algorithms to derive complex datasets and resolve data issues.
• Strong problem-solving skills, attention to detail, and collaborative teamwork.
• Excellent interpersonal and communication skills.
• Willingness to travel domestically and internationally for conferences (approximately 5–10% of the time).

Preferred Qualifications

• 2+ years of pharmaceutical industry experience preparing SAS datasets for analysis, including 1+ years preparing SAS datasets for pharmacometric analysis in NONMEM, NLME, or WinNonlin; proficiency in SAS or R, with certification in either a plus.
• Familiarity with CDISC standards and quality control principles.
• Hands-on experience with AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot).