Senior/Staff Scientist, Cheminformatics & Data Science at Deep Origin

, , United States -

Full Time

Start Date

Immediate

Expiry Date

25 Dec, 25

Salary

0.0

Posted On

26 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Cheminformatics, Machine Learning, Drug Discovery, Python, RDKit, Scikit-learn, PyTorch, Data Curation, Predictive Models, Protein-Ligand Interactions, Molecular Design, Cloud Platforms, Workflow Orchestration, Ligand Docking, Data Quality Control, Chemical Datasets

Industry

Biotechnology Research

Description

Deep Origin is seeking a Senior or Staff Scientist with strong expertise in cheminformatics, machine learning, and drug discovery to join a groundbreaking initiative funded by ARPA-H. This is a rare opportunity to help define and deploy scalable computational models for predicting protein-ligand binding, enabling next-generation therapeutics. You’ll work with a multidisciplinary team of scientists and engineers to lead ligand- and structure-based modeling efforts, contribute to data curation, and develop high-performing predictive models that accelerate molecular design. Ph.D. in cheminformatics, computational chemistry, chemical biology, or a related field; 2+ years of industry experience in drug discovery or pharmaceutical data science; Deep familiarity with protein-ligand interactions, protein structure handling, and ligand representations; Strong proficiency in Python, with hands-on experience using RDKit, scikit-learn, PyTorch, or similar frameworks; A strong foundation in ML model development, validation, and interpretability. Nice to have: Experience working with DNA-encoded libraries datasets, including data quality control and preprocessing; Exposure to protein structure analysis, scoring functions, or ligand docking workflows (e.g., AutoDock Vina, etc.); Familiarity with cloud platforms (AWS, GCP) and workflow orchestration tools. Responsibilities: Design, curate, and process diverse chemical and biological datasets (ChEMBL, BindingDB, RCSB PDB, UniProt, etc.); Build and evaluate ligand-based ML models (e.g., QSAR) using methods like gradient-boosted trees, neural nets, and graph neural networks (GNNs); Incorporate structural features of proteins and ligands into affinity prediction workflows; Collaborate closely with medicinal chemists, biologists, and data scientists to support data-driven discovery decisions; Plan and organize work to meet key deadlines and milestones; coordinate with collaborators to ensure integration with broader project efforts; Communicate effectively within Deep Origin and with external partners, regularly sharing updates on progress, blockers, and decisions; Clearly communicate model performance, limitations, and insights to both technical and non-technical teams. Why Join Deep Origin Deep Origin builds cloud-native tools for scientists working on the frontiers of biology, chemistry, and computation. We’re mission-driven and deeply collaborative, your work will directly impact how therapeutics are discovered and optimized. As part of this ARPA-H initiative, you'll have the opportunity to operate at the cutting edge of scientific infrastructure and translational impact. We offer: A remote-friendly environment (with hubs in the US and Armenia); Competitive compensation and equity packages; Flexible schedules; A culture that encourages curiosity, autonomy, and creative problem-solving. Apply now and help accelerate the future of therapeutic discovery.

Responsibilities

Design and curate diverse chemical and biological datasets while building and evaluating ligand-based machine learning models. Collaborate with multidisciplinary teams to support data-driven discovery decisions and communicate effectively on project progress.