This position can be based from any of our campus cities but can also be remote!

Enterprise Instructors at Galvanize are thought leaders in their field, who facilitate adult learning for in-person, blended, and bespoke course offerings. From Day One, you will have the opportunity to lead by example - where you will immerse students in modern software development methodologies. In addition to instructing, you will serve as a mentor and a coach to your students by delivering lectures, guiding individual and pair programming activities, whiteboarding, leading inquiry, and providing custom feedback to each learner in both individual and team environments. 

Galvanize is a dynamic learning community for technology. Our community is where people and companies with the guts and smarts to create real-world change congregate and inspire each other. Our goal is to make opportunities in technology available to all those with the aptitude, determination and drive. Across our 9 beautifully designed urban campuses (Austin, Boulder, Denver, Los Angeles, New York, Phoenix, San Francisco, or Seattle), we offer a unique combination of education, workspace and networking.

We are growing our enterprise data science instructional team at Galvanize. Our Instructors train technical professionals with programming experience to solve data science problems by utilizing innovative educational techniques. We’re looking for passionate educators and practical problem solvers with demonstrated flexibility and curiosity. We are seeking Lead Data Science Instructors for our enterprise team, with domestic and international delivery travels. Join us in building the world's hub for education in data science and data engineering. While this position can be based from any of our campus cities, we are also open to remote candidates! Regardless, this position will require approximately 35% travel.

Responsibilities

• Develop state-of-the-art, industry relevant, curriculum and deliver at large enterprises. Curriculum scope will be around machine learning, data science, and data engineering,
• Lead lectures, class activities, and mentor students during industry-aligned project work
• Deliver technical lectures on topics such as: Python, SQL, probability, statistics (Bayesian and frequentist), machine learning techniques, 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; 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, etc.

Professional Development

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. Rub shoulders and cross-pollinate
• Keep your skills sharp while working with fortune 500 clients by helping translate and solve their top business problems into solvable data and modeling technique. Become the best instructor you can be with ongoing training and support

Qualifications

• 5+ years practical industry experience as a data scientist 
• Strong understanding in the topics such as: Python, probability theory, applied statistics (Probability, A/B Testing, Bayesian methods, Regression methods, Time Series Analysis), SQL and Advanced Data Retrieval Techniques, Advanced Machine Learning (Decision Trees, Random Forest, Boosting, Support Vector Machines, Clustering, Natural Language Processing, Recommenders, Graphs), Neural Network, Reinforcement Learning, Data Engineering (Hadoop, Hive, and MapReduce), Data Visualization techniques
• Outstanding communication skills
• Multiple years of experience teaching a quantitative subject preferred
• [Plus] Master's or PhD in a quantitative discipline such as engineering, statistics, or mathematics
   

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.