- Location
- , US
- Seniority
- Senior
- Experience
- 2+ years
- Education
- PhD
- Closing date
- Today
- Source
- iCIMS
Description
Overview
Senior Scientific Analyst - Cheminformatics AI/ML
Position Purpose: We are recruiting a skilled cheminformatics professional who can integrate chemistry, cheminformatics, pharmaceutics, and machine learning to enable in-depth analysis of synthetic chemistry, pharmaceutics, and related markets. This is a domain expert role that requires strong scientific background and is able to conduct in-depth cheminformatics-related analysis and data management.
Responsibilities
Duties and Responsibilities:
- Build, maintain, and enable efficient search and analytics across large chemical databases and datasets, including data ingestion, indexing, similarity analysis and high-performance search.
- Develop and apply agentic AI solutions for drug and pipeline analytics, including autonomous or human-in-the-loop workflows that integrate scientific literatures, data analysis, and computational tools.
- Stay updated with emerging trends in computational chemistry and machine learning as applied to pharmaceutical drug development and market analytics.
- Communicate and work effectively with technical leaders on complex, expert-level technical projects and matters
Qualifications
- Master’s degree is required, preferably a Ph.D. in chemistry, computational chemistry, cheminformatics, or related scientific or technical field, with 2+ years of experience in pharmaceutical or biotech setting preferred.
- Strong expertise in cheminformatics toolkits. Demonstrated experience managing and searching large chemical databases and datasets using scalable data engineering and high-performance search technologies.
- Experience applying machine learning and developing agentic AI systems in drug and pharmaceutical analysis.
- Adequate knowledge of the pharmaceutical and CRDMO (Contract Research Development and Manufacturing Organization) industry.
- Strong communication and interpersonal skills; ability to work effectively with interdisciplinary groups.
Skills
Machine LearningData Engineering