Principal Scientist, Data Science – R&D, Therapeutics Development & Supply

• Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing Therapeutics Development & Supply data
• Create and optimize structured and unstructured data flows using Python, R, SQL, DBT, cloud services, and modern engineering tools
• Develop and maintain TDS-specific data repositories and enterprise-level data models
• Ensure data is structured, versioned, traceable, and semantically aligned for AI/ML readiness
• Translate business needs into high-quality data products and engineering requirements with data scientists, domain experts, and digital technology teams
• Implement semantic models and future-proof data architectures with ontology and knowledge graph teams
• Define data quality and performance standards and KPIs for TDS data assets
• Apply data versioning and lineage tracking for compliance, traceability, and audit readiness
• Follow software development best practices, including code versioning, DevOps integration, and documentation
• Engage scientific, technical, and operations stakeholders to understand requirements, design solutions, and drive adoption
• Support multiple concurrent projects, manage priorities, and deliver business value across the TDS network

Requirements

• Advanced degree in Engineering, Data Science, Life Sciences, Computer Science, or related field
• 3+ years of experience in data engineering, including data modeling and database design
• Proficiency with Python, R, SQL, and cloud-based architectures such as AWS services, Snowflake, and Redshift
• Experience with NoSQL and graph databases
• Strong analytical and problem-solving skills
• Strong stakeholder-management skills and ability to translate discussions into actionable requirements
• Ability to drive multiple projects simultaneously
• Strong organizational skills and adaptability
• Preferred: experience with regulated or standards-driven data environments, including CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards
• Preferred: familiarity with high-dimensional data such as imaging and sensor data
• Preferred: experience with MLOps and model deployment workflows
• Preferred: knowledge of manufacturing systems, laboratory information systems, or industrial data systems
• Preferred: experience with knowledge graph architectures

Core Competencies

Demonstrates expertise in designing and maintaining scalable data pipelines, ensuring data quality and compliance for Therapeutics Development & Supply. Proficient in utilizing Python, R, SQL, and cloud architectures to create high-quality data products and support AI/ML readiness.

Highest-signal resume keywords

• Data Engineering
• Python Programming
• SQL Proficiency
• Cloud-Based Architectures
• Stakeholder Management

ATS Optimization Keywords

Hard Skills

• Data Modeling
• Database Design
• Data Versioning
• Data Lineage Tracking
• MLOps
• Graph Databases
• NoSQL Databases
• Data Quality Standards
• Data Integration
• Data Architecture

Soft Skills

• Analytical Skills
• Problem-Solving Skills
• Organizational Skills
• Adaptability
• Communication Skills

Industry Keywords

• Therapeutics Development
• Data Compliance
• CDISC
• HL7
• FHIR
• OMOP
• DICOM
• Quality Data Standards
• Regulated Data Environments
• Data Products

Tools & Technologies

• AWS Services
• Snowflake
• Redshift
• DBT
• Ontology
• Knowledge Graphs
• DevOps Tools
• Laboratory Information Systems
• Manufacturing Systems
• High-Dimensional Data