Lead Instructor, Principal Data Scientist
Galvanize, San Francisco
The learning community for technology
As a Data Science instructor at Galvanize, you will:
- Deliver lectures and tutorials on scientific Python, SQL, probability, statistics (Bayesian and frequentist), machine learning, and data engineering.
- Lead day-long “sprints,” maintaining a strong presence in the classroom and managing other instructional staff.
- Deftly and patiently field student questions and provide feedback in lectures and office hours.
- Build and refine data science curriculum and assignments.
- Utilize student feedback and experimentation to continuously improve teaching and assessment methods.
- Evaluate new tools, packages, and tutorials for use in the curriculum.
- Contribute to local evangelism, admissions, and nurture activities, such as attendance at meetups, speaking at conferences, leading workshops (day time and/or evening), etc.
- At Galvanize, we strive to provide meaningful professional development opportunities to all of our employees. Here are just a few of the ways you will continue to grow and “level-up” as a data scientist and a teacher:
- There’s no better way to learn than to teach! You’ll be amazed at how much you’ll develop skills you thought you were already an expert in just by helping students and planning lessons.
- Opportunities to work with and learn from other data science and web development instructors in a highly collaborative and intellectually rich environment.
- Previous projects have involved: Machine Learning, Deep Learning, Data Engineering and Architecture, Applied Statistics and Statistical Modeling.
- Become the best instructor you can be with ongoing training and support.
- Multiple years of experience in industry in a Data Scientist or Software Engineer role
- Master's or PhD in a quantitative discipline such as engineering, statistics, or mathematics
- Strong understanding in the topics we teach: scientific Python, probability, statistics (Probability, A/B Testing, Bayesian methods, Regression methods, Time Series), SQL, Machine Learning (Decision Trees, Random Forest, Boosting, Support Vector Machines, Clustering, Natural Language Processing, Recommenders, Graphs), Data Engineering (Hadoop, Hive, and MapReduce), Data Visualization (d3), and data at scale.
- For more details on the program go to: http://www.galvanize.com/courses/data-science/#.Viqz4LQR8UU
- Outstanding communication skills
- Multiple years of experience teaching a quantitative subject strongly preferred
Galvanize is a 21st Century school for entrepreneurs, engineers, and data scientists. On eight campuses across the U.S., the energy, intellect and ambition of Galvanize students, members and alumni are at the heart of a learning community that promotes belonging, and that celebrates courage and growth.