Principal Scientist, Data Science (Data Products, Integration & Analysis)

Description

This Principal Scientific Data Scientist role sits in Data Analytics & Computational Sciences, within the Data Science sub-function and the Scientific/Technology category, at a healthcare company's Innovative Medicine area.

You will lead the design, build, and ongoing evolution of scientific data products and integration strategy for AI-enabled drug discovery and development.

You will create scalable, interoperable, AI-ready data products that link discovery, preclinical, clinical, safety, and real-world evidence data, including validated biomarker data assets.

You will set the data architecture, integration strategy, metadata framework, and productization approach behind semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI.

You will work with scientific stakeholders, knowledge architects, AI engineers, and the Amazon BioDiscovery platform teams to define the future scientific data ecosystem and deliver high-quality data products for translational science and patient safety.

You will also build AI reasoning models that support data-driven translational safety decisions.

Mission: make AI-ready scientific data products that let data be integrated, harmonized, and reused across the drug discovery and development lifecycle.

Responsibilities

• Define and run a scientific data product strategy covering discovery research, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
• Build reusable, scalable data products for analytics, AI, knowledge graphs, and scientific reasoning, and set product roadmaps that match organizational priorities and scientific goals.
• Design frameworks that connect varied scientific data sources, and define how SEND, SDTM, ADaM, MedDRA, imaging, omics, biomarker, pathology, and real-world data are harmonized.
• Create architecture patterns that make data interoperable across domains.
• Set the AWS implementation strategy for scientific data products, and work with Amazon engineering and platform resources on scalable pipelines and data products.
• Provide technical direction and architecture oversight for implementation, following Data Strategy group recommendations and keeping to enterprise architecture, security, governance, and AI-readiness requirements.
• With the Data Strategy group, lead the design and build of curated datasets, semantic-ready products, feature stores, metadata products, scientific data services, and AI-ready assets.
• Set reusable patterns for onboarding, transforming, validating, and publishing data.
• Define metadata standards and data quality frameworks, implement lineage, provenance, traceability, and FAIR principles, and set up monitoring and quality controls.
• Build predictive AI and ML models to support translational safety decisions.
• Work with discovery scientists, toxicologists, clinical and safety scientists, data scientists, Data Strategy partners, knowledge architects, and AI engineers, turning scientific questions into scalable data products and technical solutions.

Requirements

• Master's or PhD in computer science, data engineering, bioinformatics, biomedical informatics, information systems, computational biology, or a related scientific discipline.
• At least 5 years of experience in scientific data engineering, data architecture, data products, or life sciences informatics.
• A proven record of designing and delivering enterprise-scale scientific data products.
• Experience supporting drug discovery, development, clinical research, or pharmacovigilance organizations.
• Experience developing predictive models in drug discovery, development, clinical research, or pharmacovigilance.
• Strong skills in data architecture, data modeling, data product design, cloud-native data platforms, metadata management, data governance, and predictive model development.
• Hands-on experience with AWS data platforms, data lakes and lakehouses, distributed data processing, APIs and data services, and data cataloging and lineage tools.
• Strong familiarity with SEND, SDTM, ADaM, and MedDRA.
• Preferred: familiarity with FHIR, OMOP, DICOM, and biomarker and omics data standards.
• Preferred: experience supporting knowledge graphs, semantic architectures, or GraphRAG initiatives.
• Preferred: experience building AI-ready data products and feature stores.
• Preferred: familiarity with ontology-driven data integration.
• Preferred: experience working with cloud providers or external platform teams.
• Preferred: experience operating in highly regulated scientific environments.
• Preferred skills: advanced analytics, coaching, critical thinking, data analysis, data privacy standards, data quality, data reporting, data savvy, data science, data visualization, digital fluency, econometric models, organizing, process improvement, strategic thinking, technical credibility, and workflow analysis.
• Think strategically about long-term data product roadmaps.
• Communicate clearly across scientific and technical communities.
• Influence cross-functional teams without direct authority.
• Execute with a focus on scalable, reusable solutions.
• Be motivated to transform biomedical R&D through data, AI, and modern engineering practices.

Conditions

Hybrid work model, with the role based in Horsham, Pennsylvania; Raritan, New Jersey; Spring House, Pennsylvania; or Titusville, New Jersey.

Anticipated base pay range is $117,000.00 to $201,250.00.

The company welcomes accommodation requests for the interview process from applicants with disabilities.

Benefits

• Eligibility to join the company's consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
• Eligibility for the long-term incentive program.
• 120 hours of vacation per calendar year.
• 40 hours of sick time per calendar year, or 48 hours in Colorado or 56 hours in Washington.
• 13 days of holiday pay per calendar year, including floating holidays.
• Up to 40 hours per calendar year of work, personal, and family time.
• 480 hours of parental leave within one year of the birth, adoption, or foster care of a child.
• 240 hours of bereavement leave for an immediate family member and 40 hours for an extended family member per calendar year.
• 80 hours of caregiver leave in a 52-week rolling period, and 10 days.
• 32 hours of volunteer leave per calendar year.
• 80 hours of military spouse time off per calendar year.