Deep Origin is a biotechnology company accelerating drug discovery through AI-powered tools. Our platforms simplify R&D, simulate biology, and empower scientists to solve diseases and extend human healthspan through software solutions and partnerships. We integrate advanced computational methods with experimental data to model biological systems at scale.

About the Role

We are seeking a motivated scientist to extract, review, validate, and organize chemistry and drug metabolism data from scientific literature and public databases. You will play a key role in building high-quality datasets that power Deep Origin’s AI models for drug metabolism, enzyme kinetics, and pharmacokinetic prediction.

Working closely with computational scientists and software engineers, you will extract, validate, and organize experimental metabolism data, ensuring accuracy, consistency, and scientific rigor. This role is ideal for someone with a strong chemistry or pharmaceutical sciences background who enjoys scientific literature review, data organization, and attention to detail.

Requirements

• Bachelor’s degree in Chemistry, Pharmaceutical Sciences, Biochemistry, Biology, or a related scientific discipline
• Strong understanding of organic chemistry and basic enzymology
• Familiarity with scientific literature and experimental methods in drug metabolism
• Excellent attention to detail and organizational skills
• Ability to accurately interpret tables, figures, and experimental methods from scientific publications
• Experience working with spreadsheets and structured datasets
• Strong written and verbal English communication skills
• Ability to work independently while collaborating within a multidisciplinary team

Preferred Qualifications:

• Coursework or laboratory experience in drug metabolism or pharmacokinetics (DMPK)
• Familiarity with drug-metabolizing enzymes (CYP, UGT, SULT, NAT, etc.)
• Experience with scientific databases such as ChEMBL, PubChem, DrugBank, or similar resources
• Basic scripting experience (Python or R) for data handling is a plus
• Prior experience with scientific data curation or literature review.

Responsibilities:

• Curate experimental drug metabolism kinetic data from peer-reviewed publications and public databases
• Extract and annotate metabolic pathways, metabolite structures, and biotransformation reactions
• Curate experimental kinetic parameters including Km, Vmax, kcat, intrinsic clearance (CLint), half-life, and related experimental measurements
• Record experimental metadata including enzyme source, assay conditions, species, tissue, substrate concentration, and analytical methods
• Evaluate literature for data quality, consistency, and completeness
• Standardize chemical structures, units, nomenclature, and experimental annotations
• Perform quality control and validation of curated datasets
• Work closely with computational scientists to improve data quality and identify gaps in available experimental data
• Maintain well-documented, reproducible curation workflows

Why join us?

• Work on impactful problems at the frontier of AI + chemistry + biology
• Collaborate with multidisciplinary teams of scientists
• Shape next-generation tools for predictive drug discovery.

Benefits

• Health insurance for you and your family.
• Additional leave days added to your annual paid time off.
• Weekly highly specialized seminars on bio-machine learning and chemistry.
• Collaborating with highly experienced professionals.
• Salary with equity, including stock options after probation.