Octant Verified

Biotechnology

Scientist, Discovery Cheminformatics

RemoteRemoteFull Time$145,000–$185,000 /yrPosted 21 days agoVisa sponsorship available

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Required skills

cheminformatics
machine learning
drug discovery
medicinal chemistry
Python
NumPy
pandas
Polars
cloud infrastructure
databases

Nice to have

AI/ML
generative chemistry
computational strategy
chemical libraries
hit-to-lead
data and computational infrastructure

Role summary

Octant is seeking a Scientist with expertise in cheminformatics and machine learning to drive small molecule drug discovery programs. This role involves analyzing data, developing predictive models, designing chemical libraries, and contributing to computational infrastructure. The ideal candidate will have 2+ years of drug discovery experience, deep cheminformatics knowledge, applied ML experience, strong Python skills, and familiarity with cloud infrastructure. The position offers a competitive salary and benefits, with a remote work option available.

COMPANY

Octant is a clinical-stage drug discovery company developing correctors for protein misfolding diseases with active programs in rare diseases and oncology. Octant’s platform, The Navigator, combines high-throughput synthetic biology, generative chemistry, and AI/ML to discover and develop therapeutics against complex cellular mechanisms in human cells.

JOB DESCRIPTION

Octant is seeking a scientist with a strong background across the chemical and computational domains. You will apply established and emerging cheminformatics and machine learning methods to drive Octant’s small molecule drug discovery programs. This is a unique opportunity to leverage and shape our iterative, direct-to-biology chemical synthesis platform and expansive datasets, all in the context of live programs.

In this interdisciplinary role, you will engage the chemistry and biology of our programs through a computational lens. You are motivated by the mission of Octant and have a team-first mindset. You bring excellent communication skills and an ability to thrive in a dynamic and fast-paced environment.

IN THIS ROLE, YOU WILL:

Lead cheminformatics on multiple drug discovery programs, analyzing data with medicinal chemists and biologists each week and shaping which compounds get made.

Expand Octant’s cheminformatics and ML capabilities, including methods for iterative exploration of chemical space, development of predictive ADME models and scoring functions, and help set our long-term computational strategy as the field moves.

Collaborate with chemists to design and test chemical libraries on our nanoscale and microscale synthesis platform, guiding hit-to-lead and lead optimization.

Develop and contribute to the data and computational infrastructure, enabling scientists to access and analyze their own data in consistent, statistically rigorous ways.

Increase scientist leverage by building the agentic layer of our discovery workflows: encode cheminformatics methods as tools that AI agents use to propose, triage, and analyze compounds alongside program scientists with the appropriate strategies and safeguards for decision making.

THIS JOB MIGHT BE GREAT FOR YOU IF YOU HAVE:

An advanced degree (preferably a PhD) in chemistry, computer science, statistics, or a related field.

2+ years of drug discovery experience, academic or industry.

Working knowledge of medicinal chemistry: you can reason about structure-property relationships and be fluent chemically in discussions with chemists.

Deep cheminformatics expertise (SAR analysis, library enumeration, property calculation) and fluency with the standard toolkits (e.g. RDKit, Datamol, OEChem).

Applied machine learning to chemical problems, including QSAR or property models that were deployed and used on live programs; comfort with the relevant stack (e.g. PyTorch, JAX, scikit-learn, DeepChem).

Experience working side-by-side with medicinal and computational chemists, data scientists, and engineers, including influencing which molecules get made; an instinct for building analyses and tools that scientists can run themselves.

Strong software skills: fluent in Python and its data stack (NumPy, pandas, Polars), experienced with cloud infrastructure, databases, and version control; writes reproducible analyses that other people can run and build on.

Familiarity with structure-based computational chemistry methods (protein structure analysis, docking, MD) and interest in going deeper.

Experience curating public chemical datasets (e.g. ChEMBL, PubChem) and using them to augment internal models.

Built tooling and infrastructure for agentic workflows.

Optional: Along with your application, please share a paper/preprint/software repo that best highlights your strengths so we can better understand work you've led. If there is nothing public, please summarize that work in a few paragraphs. We'd love to also hear about things you've been proud to build or lead outside of science.

The expected annual salary for this role is in the range of $145,000 to $185,000, depending on experience level. We offer health benefits (medical, dental, vision), equity, and 401(k) matching.

Octant is located in Emeryville, California. We primarily work onsite, but are open to remote hires for this role.

Octant is an equal opportunity company that values applicants of all backgrounds. We’re committed to fostering an inclusive and supportive work environment. We value less traditional backgrounds, and may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. We know that confidence-gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.

OCTANT’S NAVIGATOR PLATFORM:

Octant’s Platform, “The Navigator,” accelerates the design, build, test, & learn iterations across chemistry and biology to build drugs against cellular mechanisms. The Navigator is an expanding set of drug discovery and development capabilities with three interwoven components that operate together:

Generative Biology – Multiplexed measurements from engineered sensors in human cells to understand cellular mechanisms

Generative Chemistry – Nanoliter-scale chemical synthesis for rapid exploration of local & targeted chemical space

Generative AI – ML/AI ingests large-scale biological and chemical datasets and drives iteration of experiments to build better molecules faster

Together, the Navigator platform drives week-to-week progress on our drug programs, generating 3M+ readouts each week across multiple therapeutic areas.

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