Senior Specialist, Data Science / Modeling & Informatics
About The Position
Merck’s multidisciplinary Research and Development organization combines scientific expertise and resources to discover and develop medicines and vaccines. Modeling and Informatics is an approximately 50-person group of computational chemists and data scientists within global Discovery Chemistry, applying structure-based modeling and predictive science to drug design and development. The Senior Specialist will join the Research Laboratories in South San Francisco, California. This on-site role develops algorithms, tools, and workflows that integrate predictive modeling, agentic scientific reasoning, and physics-based insight. The successful candidate will help build next-generation systems that reason across multiple data sources, assess molecular hypotheses, and learn from experimental feedback throughout the Design-Make-Test-Analyze cycle. The role involves in-person collaboration and is not remote.
Requirements
- Bachelor’s degree with 7 or more years of relevant experience, Master’s degree with 4 or more years of relevant experience, or Ph.D. (or Ph.D. completion by June 2027) in Engineering, Computer Science, Machine Learning, Chemistry, Computational Chemistry, Biophysics, Applied Mathematics, or a related discipline.
- At least two years of hands-on experience, including experience obtained during education, developing, training, and evaluating deep-learning models using a framework such as PyTorch or JAX.
- Broad competency in modern data science.
- Research experience applying deep-learning approaches to chemistry or biophysics problems.
- Experience with agentic AI frameworks.
- Track record of scientific publications in peer-reviewed journals.
- Strong Python skills for scientific programming, methods development, and algorithm development on Linux high-performance computing.
- Excellent written and oral communication skills.
Nice To Haves
- Experience with AI/ML methodologies relevant to molecular design, such as graph neural networks, transformers, diffusion models, generative modeling, reinforcement learning, active learning, or molecular foundation models.
- Experience with agentic AI frameworks such as LangChain, LangGraph, or similar.
- Experience with cheminformatics tools such as RDKit.
- Experience with 3D molecular modeling and physics-based computational methods, such as protein-ligand modeling, structure-based molecular design, molecular dynamics, or quantum chemistry.
- Scientific software-engineering experience translating research algorithms into robust, reproducible computational workflows.
- Experience collaborating directly with experimental scientists.
Responsibilities
- Develop novel AI/ML algorithms and computational methods for molecular representation, prediction, generation, reasoning, and decision-making, including components for AI co-scientist and autonomous molecular-design systems.
- Evaluate AI/ML methods rigorously against computational and experimental benchmarks, addressing scientific validity, uncertainty, robustness, baselines, failure modes, and prospective utility.
- Develop and apply deep-learning approaches for molecular discovery that combine machine learning with physical and biophysical understanding, including molecular interactions, conformational energetics, thermodynamics, kinetics, solvation, molecular recognition, and structure-function relationships.
- Develop agentic workflows integrating predictive models, scientific tools, experimental data, simulations, structural information, SAR, and scientific literature to generate and critically evaluate molecular hypotheses.
- Collaborate with medicinal and computational chemistry project teams to apply AI/ML and computational approaches to molecular design, SAR interpretation, hypothesis generation, and experimental prioritization.
- Build reproducible scientific methods and workflows, pilot approaches on active drug-discovery programs, and work with colleagues to deploy successful methods across computational environments and broader discovery platforms.
- Conduct innovative research in computational chemistry, computer science, biophysical chemistry, and molecular modeling relevant to drug discovery, and contribute through publications and presentations.
- Mentor scientists and help expand organizational capabilities in data-driven molecular design, computational methodology, and scientific reasoning.
Benefits
- Medical, dental, and vision healthcare and other insurance benefits for employees and their families.
- Retirement benefits, including 401(k).
- Paid holidays, vacation, compassionate days, and sick days.
- Eligible for an annual bonus and long-term incentive, if applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
