We’re looking for Molecular Data Scientists to use their interdisciplinary background in chemistry and computer science to build tools, visualizations, and analyses that enable our team to create life-saving cures. At Reverie, Molecular Data Scientists work side-by-side with ML engineers, computational chemists and medicinal chemists to achieve drug discovery objectives. We are looking for mission-driven individuals that are eager to bring ideas from conception to reality.

Do the following sound challenging and fun to you? If so, we’d love to hear from you!

• Using tools like RDKit, Openeye, Amber, and other computational chemistry packages to generate chemical representations that can be used for machine learning.
• Developing Jupyter notebooks to analyze a variety of molecular datasets, using software to extract drug discovery insights like activity cliffs, selectivity hypotheses, and predicted binding modes.
• Combining a set of 25+ in-house experimental assays and 50+ external data streams into a universally accessible data platform.
• Working hand-in-hand with chemists to understand compounds by building tools and visualizations that reflect dataset statistics.
• Developing outlier detection mechanisms to determine whether a data point is likely the result of experimental error.
• Using a modern cloud-first development stack to get access to effectively infinite computing power.

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We don’t have a hard set of background requirements, but we highly value skills and experience in the following areas:

• Chemistry-related programming skills: 2+ years experience building tools with widely-used chemistry packages like RDKit, Openeye, etc.
• Visualization: Expert level knowledge of compound and protein visualization tools like PyMol. Non-python tools like R are also valued.
• Statistical knowledge: Knowledge of probability distributions, sampling methods, and other statistics concepts.
• Biotech/Pharmaceutical experience: We are looking for applicants with 3+ years of industry experience or deep technical expertise in an academic setting.
• Applicants with experience and insight from Computational Biology or Genetics are also encouraged to apply.
• Most importantly, an eagerness to learn new skills, wear many hats, and collaborate closely with a growing team of people.

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