Principal Research Scientist II- Data Architecture, Biotherapeutics and Genetic Medicine

Role Summary

The Principal Data Architect is a visionary leader in the development and success of a cloud-native data platform supporting predictive and generative machine learning solutions in drug discovery workflows. The role requires balancing the big picture with detailed execution across cross-functional teams, including wet lab scientists, ML engineers, software engineers, data engineers, and data infrastructure engineers. It reports to the Head of AI/ML in Biotherapeutics and Genetic Medicine and serves as a trusted advisor to senior leadership, driving the organization toward leadership in AI with a robust, scalable data foundation.

Responsibilities

• Drive the vision, execution, implementation, adoption, and continuous improvement of a robust, scalable data platform as the foundation for AbbVie's AI/ML strategy within BGM.
• Define data models and architectures to collect, store, structure, access, and connect datasets across multiple lab groups for downstream uses (ML model development, operational reports, lab documentation, etc.).
• Collaborate with wet lab scientists and automation engineers to maximize utility of data from lab automation workflows.
• Collaborate with data scientists and deployment engineers to ensure data pipelines support model development and production deployment.
• Co-develop and execute a strategy to maximize FAIR data principles within BGM and align with broader goals.
• Communicate the impact of the data platform to AbbVie’s drug pipeline using user stories and KPIs to measure value.
• Champion connected data, data stewardship, data-as-a-product, and cloud-first architectures to amplify platform impact.
• Collaborate with data infrastructure and governance experts to implement data governance principles and policies.
• Align data infrastructure initiatives with AbbVie programs (e.g., Convergence, ARCH).

Qualifications

• BS, MS, or PhD in computer science, data science, computational biology/chemistry/biophysics, or related field with typically 16+ (BS) years, 14+ (MS) years, or 8+ (PhD) years of experience in data architecture and enterprise data platform design.
• Deep technical skills in data modeling, data integration, storage solutions, data pipelines, and AI/ML integration.
• Production programming expertise in SQL, Python, or Java.
• Experience building cloud data infrastructure solutions on AWS, Azure, or GCP.
• Familiarity with both wet and dry lab principles; ability to anticipate and prevent data platform-originating failure modes.
• Experience leading cross-functional teams and a track record of collaboration excellence.
• Previous experience in the pharmaceutical or biotechnology sectors.
• Experience managing both delivery and career development of team members.
• Strong interpersonal and communication skills with ability to build stakeholder alignment.
• Ability to incorporate data governance principles into everyday decision making.

Skills

• Data governance and data stewardship
• Cloud-native architectures and data platforms
• Data modeling, integration, and pipeline design
• Stakeholder management and cross-functional collaboration
• Communication of data-driven value using KPIs and storytelling

Education

• BS/MS/PhD in computer science, data science, computational biology, computational chemistry, computational biophysics, or related field

Additional Requirements

• Location: Worcester, MA site; full-time in-office or hybrid (3 days per week)