The Scientist, Machine Learning AI is responsible for researching, designing, developing, and implementing advanced artificial intelligence and machine learning models to solve complex business and technical problems. This role involves analyzing large datasets, developing predictive algorithms, conducting experiments, evaluating model performance, and optimizing AI solutions for accuracy, scalability, and efficiency. The ideal candidate has strong expertise in machine learning, deep learning, statistical modeling, and programming languages such as Python, along with excellent analytical, problem-solving, and research skills.
- Advanced degree (M.S. or Ph.D.) in computational biology, bioinformatics, computational chemistry, biophysics, or a related field
- Hands-on experience applying machine learning to biological, chemical, or biomedical data
- Experience working with protein structure data and/or structure-derived features in a research or drug discovery setting
- Experience integrating or modeling phenotypic and multimodal datasets
- Strong Python programming skills and experience with scientific computing and machine-learning libraries
- Ability to independently execute defined project work and deliver high-quality outputs on an agreed timeline
- Develop and apply machine-learning and statistical approaches to protein structure, phenotypic, and other multimodal biological datasets
- Curate, harmonize, and quality-control structured and unstructured data from internal and external sources
- Build reproducible computational workflows for feature generation, model training, validation, and performance evaluation
- Integrate protein structural representations with phenotypic and other biological data to generate testable hypotheses and prioritize follow-up analyses
- Implement clear, maintainable analysis code and contribute to shared repositories and technical documentation
- Communicate methods, findings, and recommendations clearly to technical and non-technical stakeholders