X-Associate Instructor, Data Scientist
Instructional – Instructional Team
Practical, industry-based education is hard to access in the exciting and growing field of data science. Galvanize has a tight-knit team of data scientists, educators, and community builders that are creating a pathway onto industry’s most demanding data science teams.
We are growing our data science instructional staff at Galvanize. Our Instructors train technical professionals with programming experience to solve data science problems utilizing innovative educational techniques. We’re looking for passionate educators and practical problem solvers with demonstrated flexibility and curiosity.
This role entails contributing to the instructional team, and allows significant room for continued learning.
Join us in building the world's hub for education in data science and data engineering.
As a Data Science Associate Instructor at Galvanize, you will:
- Deliver lectures and tutorials on scientific Python, SQL, probability, statistics, machine learning, and data engineering
- Grow significantly as a data scientist through professional instruction and self-study in the concepts and tools you haven't yet mastered
- Assist with day-long “sprints,” maintaining a strong presence in the classroom and helping other instructional staff
- Deftly and patiently field student questions and provide feedback in lectures and office hours
- Experience in industry in a data scientist or software engineer role
- Master's or PhD in a quantitative discipline such as engineering, statistics, or math
- Strong understanding in the topics we teach: scientific Python, probability, statistics, SQL, machine learning, data engineering, data visualization, data at scale
- Outstanding communication skills
- Experience teaching a quantitative subject preferred
Galvanize provides equal employment opportunities (EEO) to all employees and applicants for employment. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.