Summary
Aigul Khakimova is a Senior Data Scientist based in Saint Petersburg with eight years of focused experience applying chemoinformatics and machine learning to drug design. At BIOCAD she progressed from junior to senior roles developing computational platforms, QSAR/QSPR models, chemical data curation pipelines, and code review practices that bridge research and production. Her background in organic chemistry and hands-on work with retrosynthesis, metadynamics, and quantum-chemical features gives her a rare ability to translate deep domain knowledge into predictive models for small-molecule properties and reaction outcomes. She is experienced with reproducible ML tooling (Docker, Git, DVC) and has contributed to method development such as hydroxylation site prediction and novel pharmacophore validation. Colleagues rely on her for both rigorous data-driven modeling and mentoring of developers and students. Less obvious: she combines academia-rooted research instincts with practical platform-building, making her equally effective in exploratory science and production-ready pipelines.
7 years of coding experience
3 years of employment as a software developer
Specialist degree, Organic Chemistry, Specialist degree, Organic Chemistry at Kazan Federal University, A.M. Butlerov Institute of Chemistry
English, Russian, Tatar