Senior Data Scientist
Reverie Labs (YC W18) is building a pharmaceutical company from the ground up using computation—we’re a drug company that looks and feels like a tech company. We’re a team of engineers and machine learning researchers using cutting-edge tools to design new medicines.
Skills: Git, Python
At Reverie Labs, we’re building a pharmaceutical company from the ground up using computation—we’re a biotech company that looks and feels like a tech company.
We’re looking for Senior Data Scientists to dive headfirst into our varied data sources, including both external and in-house data, and build tools, visualizations, and analyses that enable our team to create life-saving cures. At Reverie, Data Scientists will work side-by-side with ML engineers, physics-based modelers, 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 like fun challenges to you? If so, we’d love to hear from you!
- Using Pandas/R/Plotly/Dash or any other of your favorite analysis tools to extract meaningful insights from datasets.
- 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.
- Building highly-performant data processing tools to analyze billions of data points.
- Developing outlier detection mechanisms to determine whether a data point is likely the result of experimental error.
- Interfacing closely with machine learning engineers to ensure that regularly-updated datasets are clean, well-structured, and ready for weekly updates and deployments.
- Using a modern cloud-first development stack, giving you access to effectively infinite computing power.
We don’t have a hard set of background requirements, but generally we most value skills and experience in the following areas:
- Visualization: Expert level knowledge of Python-based visualization tools. Non-python tools like R are also fine.
- Statistical Knowledge: Familiarity with probability distributions, sampling methods, and other statistical concepts.
- Data Engineering: Knowledge of data pipelining and storage tools to enable large-scale data processing workflows.
- We are looking for applicants with 3+ years of industry (tech or biotech) experience or deep technical expertise in an academic setting.
- No biology/chemistry experience is required, but interest or experience is helpful!
- Most importantly, an eagerness to learn new skills, wear many hats, and collaborate closely with a growing team of people.
Finally, we base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are particularly welcomed.
Here’s a small sample of some of the hard tasks we solve to accomplish our goal of developing life-saving treatments for patients:
- Developing new machine learning algorithms and architectures to model complex biological systems.
- Translating state-of-the-art machine learning techniques designed to work on images, text, or audio into the domain of molecules.
- Creating a large-scale distributed training and hyperparameter optimization system.
- Using data mining and processing techniques to uncover new sources of data and clean our existing datasets.
- Using predictive modeling to make critical decisions about which tests to run in the lab.