As a Scientific Data Architect, you will lead the design and implementation of advanced data systems that power scientific discovery in biopharma research and development. Your work will focus on structuring complex scientific data to enable AI and machine learning applications, driving innovation from early discovery through development and quality testing.
Key Responsibilities
- Design and develop AI-native datasets tailored to scientific workflows
- Partner with scientists, engineers, and product teams to translate research needs into scalable data solutions
- Prototype and demonstrate technical approaches to accelerate product development cycles
- Conduct exploratory data analysis to uncover insights and optimize scientific processes
- Communicate technical findings effectively to both technical and non-technical audiences
- Provide expert guidance to research teams to enhance data-driven decision-making
- Develop flexible, reusable data models and applications for biopharma use cases
- Take full ownership of technical outcomes and continuous improvement
Qualifications
- PhD with at least four years or Master’s with eight or more years of relevant industry experience
- Deep understanding of drug discovery, preclinical development, CMC, or product quality across modalities
- Proven experience building AI/ML-driven solutions in cloud environments
- History of working with cross-functional teams including product, engineering, and scientific staff
- Strong skills in data analysis, workflow optimization, and data modeling
- Exceptional communication abilities with diverse stakeholders
- Ability to quickly master new technologies and scientific domains
- Commitment to accountability, ownership, and continuous learning
Technical Environment
AI/ML systems, cloud platforms, scientific data integration, and extensible data architecture.
Work Environment
This is a local position based in New York with defined flexibility. The role requires in-person collaboration and engagement within the city.
