Lead Data Scientist
Engineering | Full-time, Remote
Astronomer is the commercial developer of Apache Airflow, a community-driven open-source tool that’s leading the market in data orchestration. We’re a globally-distributed and rapidly growing venture-backed team of learners, innovators and collaborators. Our mission is to build an Enterprise-grade product that makes it easy for data teams at Fortune 500’s and startups alike to adopt Apache Airflow. As a member of our team, you will be at the forefront of the industry as we strive to make Apache Airflow the de-facto standard in data orchestration.
Astronomer’s Data Science team is at the hub of everything that happens at our company — innovation, community, and operations. We collaborate with the development team to drive a data-informed product strategy. We work with account teams to identify new opportunities for growth and customer satisfaction. We create operational platforms used by executives, finance, and operations to manage the business.
Most importantly of all, we work with the open-source community to develop resources and tools that will help data engineers and data scientists and other users of Apache Airflow to be successful.
What unites everything we do is curiosity, a love of data, a cooperative spirit, and a drive to do what it takes to get the job done.
The Lead Data Scientist will be a founding member of this new team.
What You'll Do
Perform hands-on analysis with a variety of open-source technologies (Python, Spark, SQL, Tensorflow, etc.), using Airflow as the backbone.
Work with a huge variety of different data sets — as part of real-world analytics projects with our customers, and also with data from all of Astronomer’s operational systems.
Collaborate closely with a diverse, global team of talented leaders in engineering, data, and analytics.
Lead projects, help to build the team, mentor new data scientists.
Contribute to the Airflow community and ecosystem with integrations, extensions, templates, tools, and best practices.
Help to define and prioritize new features for Airflow and the Astronomer platform.
Speak at thought-leadership events in advanced analytics, data science, and AI/ML.
Requirements
Five or more years of experience in machine learning and statistics, and in the application of predictive analytics to large, complex and disparate data sources.
Practical experience of the deployment and management of production data science pipelines.
Five or more years of experience with Python and hands-on knowledge of SQL and data management.
Experience with other analytics platforms (such as Spark, Hadoop, NoSQL), with cloud platforms, with container technologies, and with Apache Airflow.
The ability to comfortably communicate with company executives, and senior industry personnel, to provide compelling presentations and demonstrations of analytics software, and to articulate and document the business value of analytics projects.
An advanced degree in a technical subject with an emphasis on statistics, computer science and/or advanced analytics.
At Astronomer, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Astronomer is a remote-first company.