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Cheminformatics Scientist
Cheminformatics Scientist
22
Hyderabad
Job Views:
Created Date: 2025-07-11
Experience: 3 - year
Salary: upto 10
Industry: 39
Openings: 1
Primary Responsibilities :
Job Title: Cheminformatics Scientist
Location: Hybrid
Job Type: Full-time
Seniority Level: Mid to Senior (PhD or equivalent industry experience)
About the Role
A forward-looking team is seeking a technically proficient and chemistry-savvy Cheminformatics Scientist to drive innovation in reaction prediction, retrosynthesis, and condition optimization. This role is at the intersection of organic chemistry and advanced machine learning, supporting the evolution of autonomous synthesis, self-driving laboratories, and intelligent reaction planning.
Experience Requirements:
Responsibilities
Prepare and structure reaction datasets (e.g., ELNs, Reaxys, USPTO) for machine learning pipelines
Develop and improve models for forward reaction prediction and single/multi-step retrosynthesis
Design and benchmark algorithms for reaction condition recommendation, including yield and selectivity modeling
Implement both template-based and template-free approaches using reaction SMARTS, graph methods, or transformer architectures
Lead or support the development of closed-loop optimization frameworks
Collaborate cross-functionally to deploy models into production cheminformatics platforms
Communicate model results, insights, and design considerations to both technical and non-technical stakeholders
Stay up-to-date with relevant literature, tools, and methodologies
Required Qualifications
PhD in Chemistry, Cheminformatics, Computational Chemistry, Machine Learning, or a related field
Solid understanding of organic chemistry principles, synthesis strategies, and retrosynthetic logic
Experience with tools such as ASKCOS, IBM RXN, AiZynthFinder, or similar platforms
Proficiency in cheminformatics libraries like RDKit, Indigo, Open Babel, or CDK
Skilled in machine learning using Python (e.g., scikit-learn, PyTorch, TensorFlow)
Hands-on experience with reaction classification, yield prediction, or optimization models
Ability to manage and process chemical data formats (e.g., JSON, XML)
Familiarity with SQL and NoSQL databases (e.g., MySQL, MongoDB)
Understanding of Bayesian optimization, active learning, or closed-loop experimentation
Bonus Qualifications
Experience integrating ML workflows into robotic chemistry platforms or autonomous labs
Contributions to open-source projects (e.g., RDKit, ASKCOS)
Experience with advanced ML models like transformers, GNNs, or seq2seq architectures
Familiarity with cloud services (AWS/GCP) and containerization (Docker, Kubernetes)
Experience in deploying models into production or chemistry SaaS environments