Senior Scientist – Scientific Data & ML Enablement Full-time

Senior Scientist – Scientific Data & ML Enablement (Large Molecule Discovery Informatics)

In this vital role, you will enable AI-driven research across Large Molecule Discovery by designing, managing, and optimizing the scientific datasets that power machine learning applications. This role will focus on transforming complex biological and experimental data into reliable, reusable, and ML-ready assets that support model development, deployment, and long-term scalability.

Working at the intersection of data engineering, scientific informatics, and machine learning, this individual will partner with scientists, AI/ML researchers, software engineers, and data platform teams to ensure that discovery data is structured and accessible for advanced analytics and AI applications. The successful candidate will help establish scalable data models, metadata frameworks, and transformation pipelines that improve data quality, consistency, and reuse across the LMD ecosystem.

This role is ideal for someone who enjoys solving complex scientific data challenges and is passionate about building the data foundations necessary to accelerate AI-enabled drug discovery.

Core responsibilities include:

• Design and maintain scalable data models supporting machine learning, analytics, and scientific research workflows
• Create and maintain ML-ready datasets for model training, validation, and deployment
• Partner with scientists to translate experimental workflows into effective data structures and reusable datasets
• Implement metadata, lineage, and governance practices that improve data quality, traceability, and reuse
• Develop standardized approaches for biological, assay, sequencing, and protein engineering datasets
• Design and optimize data transformation workflows supporting machine learning and analytics use cases
• Support integration of data from multiple scientific systems and repositories
• Collaborate with scientists, bioinformaticians, engineers, and AI teams to accelerate AI-enabled discovery research

Basic Qualifications:

Doctorate degree PhD with 5+ years of relevant exp

Or

Master's degree and 8+ years of directly related experience

Or

Bachelor's degree and 10+ years of directly related experience

Preferred Qualifications:

Experience designing data models supporting scientific, analytical, or machine learning applications

Strong proficiency in SQL, Python, and modern data engineering platforms

Experience creating datasets for machine learning, predictive modeling, or advanced analytics

Understanding of metadata, data lineage, governance, and reproducibility concepts

Experience working with biotechnology, pharmaceutical, genomics, or life science datasets

Familiarity with scientific data platforms and research informatics environments

Strong analytical, communication, and cross-functional collaboration skills

What you can expect of us:

As we work to develop treatments that take care of others, we also work to care for our teammates' professional and personal growth and well-being.

• Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans and bi-annual company-wide shutdowns
• Flexible work models, including remote work arrangements, where possible

Apply now for a career that defies imagination

Objects in your future are closer than they appear. Join us.