Senior Scientist, Cheminformatics
Merck
Summary
Our Company is currently seeking an exceptional, highly motivated Senior Scientist, Cheminformatics to join the Modeling & Informatics group within Discovery Chemistry. The successful candidate will join multidisciplinary discovery teams to drive the development and application of advanced cheminformatics workflows, machine learning models, and data-driven methods. This role focuses on accelerating drug discovery pipelines across both small molecules and emerging modalities—such as cyclic peptides, macrocycles, and DNA-Encoded Library platforms—in close partnership with computational and medicinal chemists.
Job description
Key Responsibilities
- Computational Chemistry Partnership: Partner closely with computational and medicinal chemists on Discovery Chemistry project teams to address challenging structure-activity relationships and multi-parameter optimization
- Emerging Modalities & DNA-Encoded Library Informatics: Develop and deploy specialized informatics workflows for non-traditional modalities (cyclic peptides, macrocycles) and DNA-Encoded Library platforms, including combinatorial enumeration, selection data triage, and hit prioritization.
- Workflow & Algorithm Development: Design, validate, and implement scalable cheminformatics and machine learning pipelines for predictive property modeling, virtual screening, and chemical library triage.
- Data Infrastructure & Tooling: Establish robust, automated computational tools and data pipelines that bridge internal chemical data platforms and modern modeling frameworks.
- Scientific Presence & Mentorship: Maintain an active external scientific presence through publications, conference presentations, and community engagement, while mentoring junior staff, interns, and co-ops.
Position Qualifications
Required Education: Ph.D. (or close to completion) in Cheminformatics, Computational Chemistry, Chemistry, Computer Science, Bioinformatics, or a related quantitative discipline; OR M.S. degree with 4+ years of relevant industry/research experience.
Required Experience & Skills: Demonstrated expertise in cheminformatics fundamentals (molecular representations, fingerprints, similarity search, tautomer enumeration, and conformer generation). Strong programming proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas, scikit-learn). Extensive hands-on experience with modern cheminformatics toolkits (e.g., RDKit, OpenEye Toolkits, or CDK). Experience developing and validating machine learning or statistical QSAR models applied to chemical or biological data. Demonstrated track record of effective collaboration in multidisciplinary scientific teams. Strong oral and written communication skills, evidenced by peer-reviewed publications or presentations.
Preferred Experience: Experience with computational design of cyclic peptides, macrocycles, or non-canonical peptide representations (e.g., HELM notation). Experience with DNA-Encoded Library analysis, combinatorial enumeration, or NGS selection data deconvolution. Familiarity with molecular modeling and structure-based design tools (e.g., Schrödinger, MOE) to facilitate cross-talk with molecular modelers. Experience deploying containerized workflows (Docker), version control (Git), and utilizing Linux/high-performance computing (HPC) environments.
Requirements
- Ph.D. (or close to completion) in Cheminformatics, Computational Chemistry, Chemistry, Computer Science, Bioinformatics, or a related quantitative discipline; OR M.S. degree with 4+ years of relevant industry/research experience
- Demonstrated expertise in cheminformatics fundamentals (molecular representations, fingerprints, similarity search, tautomer enumeration, and conformer generation)
- Strong programming proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas, scikit-learn)
- Extensive hands-on experience with modern cheminformatics toolkits (e.g., RDKit, OpenEye Toolkits, or CDK)
- Experience developing and validating machine learning or statistical QSAR models applied to chemical or biological data
- Demonstrated track record of effective collaboration in multidisciplinary scientific teams
- Strong oral and written communication skills, evidenced by peer-reviewed publications or presentations
Benefits
- Medical, Dental & Vision
- 401(k) Matching
- Paid Holidays
- Vacation
- Compassionate Leave
- Sick Days
- Annual Bonus
- Long-term Incentive
Company overview
Merck & Co., Inc., known as Merck in the United States and Canada and MSD (Merck Sharp & Dohme) internationally, is a premier American multinational pharmaceutical company headquartered in Rahway, New Jersey. Founded in 1891 as the U.S. subsidiary of the German Merck Group, the company became independent following World War I and has since grown into one of the world's largest biomedical companies, ranking fourth globally by revenue. Merck operates across three core business segments: pharmaceuticals, vaccines, and animal health products. The company is renowned for its groundbreaking research and development, having brought numerous life-saving medicines to market including Keytruda (pembrolizumab), a leading immunotherapy for cancer treatment that generated $29.5 billion in 2024 revenue, and Gardasil, a revolutionary HPV vaccine. With approximately 75,000 employees worldwide, Merck maintains a robust pipeline of innovative therapies focused on oncology, vaccines, hospital acute care, cardiology, neuroscience, virology, immunology, and diabetes. The company invests heavily in R&D, spending $17.9 billion in 2024 alone, demonstrating its commitment to advancing scientific discovery. Merck's legacy spans over 130 years of bringing hope to humanity through important medicines and vaccines, operating with a purpose to use leading-edge science to save and improve lives globally while fostering an inclusive workforce and responsible business practices.