R&D Data Scientist

Role Overview

As a Data Scientist in R&D Systems & Data Governance, you will serve as a strategic technical leader bridging advanced data science and data governance. You will define, establish, and operationalize R&D wide data governance, policies, and standard operating procedures (SOPs) from a systems perspective.

What You Will Do

Your responsibilities will include authoring data policies, establishing attribute-level control and metadata management, and integrating R&D systems and data strategy. You will also design, build, and deploy machine learning and statistical models that leverage harmonized data assets from Benchling, Revvity, and Clinical platforms.

Why It Might Be a Fit

We are looking for a Data Scientist with 8+ years of experience in Data Science, R&D Informatics, or Data Architecture within Life Sciences, Biotechnology, Animal Health, or Pharmaceuticals. You should have strong programming skills in Python or R, along with advanced SQL capabilities for relational, document, and graph database querying.

Requirements

• Bachelors degree or Masters in Data Science, Computer Science, Bioinformatics, Computational Biology, Information Systems, Operations Research, or a related quantitative/life sciences discipline.
• 8+ years of relevant experience in Data Science, R&D Informatics, or Data Architecture within Life Sciences, Biotechnology, Animal Health, or Pharmaceuticals.
• Proven experience designing data governance policies, attribute-level master data management (MDM), data catalogs, data dictionaries, and enterprise data models from a systems perspective.
• Hands-on experience working with or integrating modern life science scientific platforms, specifically Electronic Lab Notebooks & Registries (e.g., Benchling), Scientific Informatics & Chemistry/Biology platforms (e.g., Revvity Signals, PerkinElmer informatics), Architecture & Enterprise modeling tools (e.g., ARCHI / ArchiMate), and Clinical data platforms (EDC, CTMS, CDISC standards).
• Strong programming skills in Python or R, along with advanced SQL capabilities for relational, document, and graph database querying.
• Demonstrated experience developing and applying statistical and machine learning models (e.g., classification, regression, clustering, NLP for scientific text, predictive modeling).
• Exceptional ability to synthesize complex data architecture and analytical concepts into actionable recommendations for scientific, operational, and executive stakeholders.

Benefits

• Multiple relocation packages
• Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
• 8-week parental leave
• 9 Employee Resource Groups
• Annual bonus offering
• Flexible work arrangements
• Up to 6% 401K matching

Tagged as: Python, SQL