Overview
On Site
Full Time
Skills
Use Cases
Manufacturing
Customer Facing
IT Management
Workflow
JSON
LIMS
Instrumentation
Data Processing
Visualization
Machine Learning (ML)
Artificial Intelligence
Prototyping
Life Sciences
Crystal Management Console
Fluency
Python
Data Modeling
Cloud Computing
Research and Development
Communication
Collaboration
Science
Job Details
Lead Scientific Data Architect
Hybrid - 4-5 days onsite in Greater Boston Area
Note: Visa sponsorship is not currently offered
Lawrence Harvey is partnering with a fast-scaling innovator at the intersection of Scientific Data and AI, working with some of the world's most influential cloud and biopharma players. This organization is setting the industry standard for how scientific R&D data is structured, modeled, and activated for AI use cases across drug discovery, preclinical development, and manufacturing quality.
We're looking for a Scientific Data Architect to help design and implement extensible, AI-native data solutions for life sciences customers. This role is ideal for someone with a strong background in life sciences (e.g., drug discovery, CMC, preclinical) and hands-on experience building production-grade data models, pipelines, and applications.
Responsibilities
Qualifications
Hybrid - 4-5 days onsite in Greater Boston Area
Note: Visa sponsorship is not currently offered
Lawrence Harvey is partnering with a fast-scaling innovator at the intersection of Scientific Data and AI, working with some of the world's most influential cloud and biopharma players. This organization is setting the industry standard for how scientific R&D data is structured, modeled, and activated for AI use cases across drug discovery, preclinical development, and manufacturing quality.
We're looking for a Scientific Data Architect to help design and implement extensible, AI-native data solutions for life sciences customers. This role is ideal for someone with a strong background in life sciences (e.g., drug discovery, CMC, preclinical) and hands-on experience building production-grade data models, pipelines, and applications.
Responsibilities
- Serve as a customer-facing technical lead, working directly with R&D teams to understand scientific workflows and translate them into scalable, cloud-based data solutions
- Architect and implement robust data models (tabular & JSON), integrating ELNs, LIMS, and lab instrumentation
- Build Python-based applications and parsers to support data processing, visualization, and integration with ML/AI models
- Collaborate closely with scientists, business analysts, and AI engineers to accelerate data activation
- Rapidly iterate on prototypes and present solutions through live demos and stakeholder meetings
Qualifications
- PhD with 7+ years or Master's with 10+ years of industry experience in life sciences domains (drug discovery, quality, CMC, etc.)
- Strong technical fluency in Python, scientific data modeling, APIs, and cloud data infrastructure
- Prior experience building data pipelines and apps used by scientists and R&D teams
- Comfortable in dynamic, fast-paced environments with a high degree of ownership
- Excellent communication and collaboration skills; able to work cross-functionally with science, engineering, and business teams
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