Temp AI/ML Scientist

The Opportunity:

Client is seeking a hands-on Contract AI/ML scientist to accelerate project work focused on TCI-ability using protein structure, phenotypic, and multimodal data. This individual contributor will partner closely with computational biology, data science, translational, and discovery teams to develop, evaluate, and apply machine-learning approaches that turn diverse biological datasets into actionable project insights. The role is time-bound and delivery-oriented, with a strong emphasis on building robust analyses, prototypes, and reusable workflows for defined program needs.

Responsibilities:

• Develop and apply machine-learning and statistical approaches for defined TCI-ability projects using protein structure data, phenotypic data, and other multimodal biological datasets.

• Curate, harmonize, and quality-control structured and unstructured data from internal and external sources; document data provenance, assumptions, and limitations.

• Build reproducible computational workflows for feature generation, model training, validation, and performance evaluation.

• Integrate protein structural representations with cellular, phenotypic, and other biological modalities to generate testable hypotheses and prioritize follow-up analyses.

• Implement clear, maintainable analysis code and contribute to shared repositories, technical documentation, and handoff materials.

• Collaborate with cross-functional scientists to translate biological questions into tractable computational workplans, milestones, and decision-ready outputs.

• Communicate methods, findings, risks, and recommendations clearly to technical and non-technical stakeholders.

• Support rapid iteration on project-specific prototypes and analyses in a dynamic discovery environment.

Required Skills, Experience and Education:

• Advanced degree (M.S. or Ph.D.) in computational biology, bioinformatics, computational chemistry, cheminformatics, computer science, data science, biophysics, quantitative biology, or a related field.

• Demonstrated 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, analyzing, or modeling phenotypic and multimodal datasets.

• Strong programming skills in Python and experience with common scientific computing and machine-learning libraries.

• Ability to build reproducible, well-documented computational workflows and clearly evaluate model performance.

• Strong problem-solving, written communication, and cross-functional collaboration skills.

• Ability to independently execute defined project work and deliver high-quality outputs on an agreed timeline.

Preferred Skills:

• Experience in oncology, drug discovery, translational research, or pharmaceutical/biotechnology R&D.

• Experience with deep learning methods for protein structure, molecular, imaging, or other high-dimensional biological data.

• Familiarity with structural bioinformatics tools, protein representation learning, or structure-based modeling.

• Experience with cloud computing, workflow orchestration, version control, and collaborative software-development practices.

• Prior experience delivering computational analyses or prototypes in a contract, consulting, or fast-paced project environment.