Chemical data scientist

Variational AI • Vancouver, BC

5d • Hybrid

About The Position

Variational AI is radically accelerating the development of promising drug candidates by integrating chemistry and pharmacology expertise with the state-of-the-art in machine learning. Traditional approaches to small molecule drug discovery require over ten years and two billion dollars, and their reliance on trial-and-error calls out for better predictive and generative models. The current industry standard has progressed little beyond shallow ML techniques and simple graph neural networks, largely due to the difficulty of integrating world-class machine learning research with traditional chemistry and pharmacology approaches. Variational AI is building a generative foundation model for molecular structure and properties from the ground up. Over the past five years, we have been advancing the state-of-the-art, and delivering projects to customers including Merck, Rakovina Therapeutics, and ImmVue Therapeutics.

We are searching for a chemical data scientist / cheminformatician to join us in our quest to radically accelerate the development of new drugs through machine learning excellence. You will help:
identify, curate, and prepare datasets, ranging from potency and ADMET to gene expression and cell painting;
characterize errors and noise in datasets, and develop techniques to filter and clean them;
analyze curated datasets and integrate chemical data into our machine learning algorithms by designing data loaders;
develop ligand- and structure-based featurizations; and
apply traditional cheminformatics techniques.
In this process, you will have the opportunity to build your skills by collaborating with our team of accomplished ML scientists, computational chemists, and medicinal chemists. No knowledge of machine learning is required for this role, but you should possess a strong interest in learning about this promising technology, coupled with a solid background in chemistry and hands-on data science experience.

Requirements

• B.S., M.S., or Ph.D. in data science, statistics, computer science, physics, or related discipline, with experience analyzing messy datasets.
• B.S., M.S., or Ph.D. in chemistry or a related discipline, with experience in cheminformatics.
• Demonstrated skill with chemical informatics including the aggregation, curation, and preparation of large experimental datasets from multiple sources.
• Strong programming skills in Python and experience with cheminformatics libraries and data analysis tools, including RDKit, Matplotlib, pandas, and seaborn.
• SQL experience preferred.
• Two or more years’ experience working in small molecule drug discovery is preferred.
• Intellectual curiosity and drive to excel.

Nice To Haves

• No knowledge of machine learning is required for this role, but you should possess a strong interest in learning about this promising technology.

Responsibilities

• Identify, curate, and prepare datasets, ranging from potency and ADMET to gene expression and cell painting.
• Characterize errors and noise in datasets, and develop techniques to filter and clean them.
• Analyze curated datasets and integrate chemical data into machine learning algorithms by designing data loaders.
• Develop ligand- and structure-based featurizations.
• Apply traditional cheminformatics techniques.

Benefits

• Compensation is a competitive mix of cash and options.
• We aim to offer competitive compensation aligned with each candidate’s experience, impact potential, and location.
• We prioritize expertise and passion over where you decide to live and work.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level