> Markdown version of [/jobs/ext/4601564-senior-specialist-data-science-modeling-informatics](https://www.wearedevelopers.com/jobs/ext/4601564-senior-specialist-data-science-modeling-informatics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Specialist, Data Science / Modeling & Informatics - **Company:** Merck & Co., Inc. - **Location:** South San Francisco, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $159,600.0 - $251,200.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Artificial Intelligence, Algorithm Design, Computer Simulation, Linux, Experimental Data, Python (Programming Language), Machine Learning, Molecular Modeling, Software Engineering, Reinforcement Learning, High Performance Computing, Graph Neural Networks, Pytorch, LangChain, Deep Learning, Generative AI, Agentic-AI, Information Technology - **Published:** November 6, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/ca/south-san-francisco/af1438f7-b00f-475a-ac81-48d891e7eec2 ## About the Role Data Science Data Modeling Deep Learning Drug Discovery Failure Causes Thermodynamics Self-Motivation Problem Solving Decision Making Active Learning Cheminformatics Computer Science Algorithm Design Machine Learning Telephone Skills Experimental Data Chemical Kinetics Scientific Methods Molecular Modeling Molecular Dynamics Workflow Management Predictive Modeling Applied Mathematics Medicinal Chemistry Software Engineering Contingent Workforce Scientific Reasoning Scientific Literature Biophysical Chemistry Reinforcement Learning Mathematical Chemistry Artificial Intelligence Computational Chemistry Verbal Communication Skills Dynamic Mechanical Analysis Graph Neural Networks (GNNs) Python (Programming Language) PyTorch (Machine Learning Library) Transformer (Machine Learning Model) At least 2 years, We are seeking an exceptional, highly motivated computational scientist to join our Research Laboratories in South San Francisco, California. The ideal candidate combines strong interpersonal and problem-solving skills with deep expertise across AI/ML, computer science, biophysics, and computational chemistry, alongside a passion for applying innovative methods to complex scientific challenges. This role focuses on building algorithms, tools, and workflows that integrate predictive modeling, agentic scientific reasoning, and physics-based insight. The successful candidate will contribute to next-generation systems that reason across miltiple data sources, critically evaluate molecular hypotheses, and continuously learn from experimental feedback throughout the Design-Make-Test-Analyze (DMTA) cycle., * Bachelor's (with 7+ years), Master's (with 4+ years) 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 and relevant experience., * A minimum of two years of hands-on experience (or experience obtained during education) developing, training, and evaluating deep-learning models using a deep-learning framework (such as Pytorch, JAX, or similar). * Broad competency in modern data science. * Research experience applying the 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 compute. * Excellent written and oral communication skills. Preferred Experience and Skills: * Experience with modern 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, including 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, including translating research algorithms into robust, reproducible computational workflows. * Experience collaborating directly with experimental scientists. #EligibleforERP, Agentic AI, Applied Mathematics, Artificial Intelligence (AI), Chemistry, Computational Chemistry, Data Modeling, Data Science, Deep Learning, LangChain (FrameWork), LangGraph, Linux, Machine Learning (ML), Molecular Modeling, PyTorch ## Description Our multi-disciplinary Research and Development organization combines state-of-the-art resources with world-class expertise in therapeutic discovery and development. We are inspired by the belief that a research-driven enterprise dedicated to scientific excellence can create medicines and vaccines that save and improve lives. Grounded in a culture of respect, invention, and collaboration, our organization offers a dynamic environment where you can build on a proud legacy of scientific breakthroughs while advancing your career., * Develop novel AI/ML algorithms and computational methods for representation, prediction, generation, reasoning, and decision-making, including methods that can serve as components of AI co-scientist and autonomous molecular-design systems. * Rigorously evaluate AI/ML methods against appropriate computational and experimental benchmarks, with an emphasis on scientific validity, uncertainty, robustness, appropriate baselines, failure modes, and prospective utility. * Develop and apply modern deep-learning approaches for molecular discovery that combine machine learning with physical and biophysical understanding of molecular systems, including molecular interactions, conformational energetics, thermodynamics, kinetics, solvation, molecular recognition, and structure-function relationships. * Develop agentic workflows that integrate predictive models, scientific tools, experimental data, simulations, structural information, SAR, and scientific literature to generate and critically evaluate molecular hypotheses. * Collaborate directly 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 new approaches on active drug-discovery programs, and collaborate with colleagues to deploy successful methods across computational environments and integrate them into broader discovery platforms. * Conduct innovative research in computational chemistry, computer science, biophysical chemistry, and molecular modeling relevant to drug discovery, and contribute to the internal and external scientific community through publications and presentations. * Mentor scientists and help expand organizational capabilities in data-driven molecular design, computational methodology, and scientific reasoning. NOTE: This role involves in-person collaborations and is an on-site position located at our research laboratories in South San Francisco, CA. This is NOT a remote role.