Location: Saturn has always been a fully-remote company, candidates in North and South America are welcome to apply
We support Visa Sponsorship for all of our roles
Saturn Cloud helps companies perform data science at a new level of scale. Our product is a SaaS platform which automates away most of the infrastructure and DevOps work needed to scale PyData code with Dask. The platform is user-friendly, scalable and secure. We want to make parallelization and cluster computing for machine learning available to any data scientist who needs it.
You will be a Data Scientist for Saturn Cloud. Data scientists here are similar to "solutions architects" at other companies. As a data scientist at Saturn Cloud, you'll work hands-on with our customers to improve the runtime, scalability, and reproducibility of their data science work.
- Work on high-visibility customer-facing projects (e.g. text and video tutorials, use-case examples, contributions to our engineering blog)
- Collaborate with customers to build proof-of-concept applications, data pipelines, or machine learning models using the PyData stack (e.g. Jupyter, pandas, numpy, dask)
- Use Saturn’s product to do data science work, and based on your experience, propose bug fixes, usability improvements, and new features to the engineering team
- Work on public content like blog posts and tutorial videos, in which you use Saturn’s product, Python, other open source software like Docker, and your own expertise to accomplish data science tasks
- Own cross-functional interactions for your projects (across eng/marketing/field/sales)
- Experience learning a new domain and using machine learning in a research setting in that domain. How you might demonstrate this:
- You hold a degree in Economics, Computer Science, Statistics, or another discipline.
- You have professional experience in a research setting like a corporate Research & Development team or in a center / lab at a university
- Excellent writer and communicator, proficient in generating engaging content. How you might demonstrate this:
- You have professional experience where you presented directly to customers or to executive audiences.
- You’ve spoken at conferences or meetups.
- You’ve taught a course or guest lectured in one.
- Experience working in an enterprise environment. How you might demonstrate this:
- You have relevant work experience where you did contract, consulting, or full-time work for a company.
- Foundational knowledge of AWS or a comparable public cloud, including some experience with object stores (e.g. AWS S3), machine learning services (e.g. SageMaker, EMR), and virtual machines (e.g. EC2). How you might demonstrate this:
- You have earned AWS certificates in the last 5 years, especially Solutions Architect, Big Data Specialty, or Machine Learning Specialty.
- You have relevant work experience where you used AWS or a comparable public cloud.
- You have used AWS as part of an open source project, personal side project, or class project.
- Proficient in Python, including the PyData ecosystem (at least two of dask, numpy, pandas, pyarrow, scikit-learn, scipy). How you might demonstrate this:
- You have professional experience where you wrote Python code to accomplish data engineering or machine learning tasks.
- You’ve made contributions to open source projects in the PyData ecosystem, including your own side projects.
- You’ve performed well in data science competitions such as Kaggle, or published Kaggle kernels.
- You’ve written blog posts which show an ability to use PyData tools to accomplish data engineering or machine learning tasks
- Comfortable reading and writing tabular data stored in files and / or databases. How you might demonstrate this:
- wrote Python code to read / write one of these file formats: CSV, feather, parquet, JSON, fixed-width, TSV
- used SQL to access data in a relational database
- You have professional experience, open source contributions, academic research, or side projects where you:
- Comfortable applying statistical techniques to business problems. How you might demonstrate this:
- You have professional experience where you used statistics to solve business problems by, for example, deploying machine learning models, writing data-drive reports, or publishing a dashboard
- You’ve published an academic paper where you applied statistics to a research question.
- Strong interpersonal skills and ability to collaborate with others. How you might demonstrate this:
- You have professional experience where you worked on projects that required collaboration with coworkers.
- You’ve done academic research where you collaborated with co-authors to produce a paper.
- You’ve co-organized a conference, meetup, or other event.
- Competitive salary commensurate with your growing experience
- Stock options in early-stage venture poised for scale
- Medical, dental, vision coverage
- 401k Retirement Plan
- Unlimited Paid Time Off (with enforced 3 week minimum)
- Awesome coworkers
- Parental leave plans
- 100% remote
- Open culture with a strong preference for asynchronous communication and respect for work / life boundaries.
Our mission is to transform the businesses of our customers by making data science faster. Saturn provides a powerful data science platform for teams to build and manage data products. We make data scientists happier and their businesses more successful. For more information, visit www.saturncloud.io.