Data Science Instructor - (Introductory Python and Data Analysis)

Key Skills

Python Programming, SQL, Big Data Technology, Data science techniques, Deep Learning, Data Analytics, R Programming

Job Description

Just as the field of Data Science is growing and ever-changing, so is our team: we’re on the hunt for talented instructors who are passionate about what they do and want to make a difference in the education of the world’s up-and-coming data scientists — our students.

The NYC Data Science Academy prides itself on housing the most comprehensive 12-week intensive boot camp in data science methodologies, providing theoretical, practical, and hands-on knowledge to our scholars. We nurture top talents in the industrial & academic world into industry-ready data scientists, by equipping them with knowledge, technical skills, and insights aiming at maximal impacts to the business world. We adapt faster than the quickest machine learning algorithms out there — with content that reflects research and application in the growing industry and teaching expertise which goes beyond extraordinary.

That’s where you come in.

From our part-time weekend/evening classes to our part-time online and full-time in-person boot camps, our courses are both designed in-house and taught by our robust team of data scientists and engineers. Instructors have the opportunity of taking part in corporate training and consulting client projects, building both data science and big data solutions. We encourage collaboration and positive change in not only our students and clients but also in our team. Nerding out is also highly encouraged.

Responsibilities

• Train in-person or online boot camp students, the next generation of data scientists, on a wide range of topics ranging from statistics, probability, SQL, R/python coding, data analysis, machine learning, deep learning, and big data, etc.
• Develop, evaluate, and maintain cutting-edge technical content for training experiences relevant to audiences with a diverse set of educational backgrounds and industry experience.
• Tailoring teaching content for both corporate and client training.
• Guide and mentor our students inside and outside of the classroom for their industry-ready projects. Help to orient our students’ learning toward the target industries.
• Lead by example as a data scientist, to be an excellent role model for our industry-ready students.
• Cooperate with marketing/admission teams by participating in the student enrollment/admission procedure and by developing relevant content for them.
• Participate in periodic training workshops to sharpen the relevant skill-sets.

About You

• Minimum of a Master’s Degree in a Quantitative Science, Technology, Engineering, or Mathematics-related field; Computer Science and Statistics preferred.
• Proficiency in statistical computing/machine learning and/or programming in Python

• Experience/extensive knowledge in Python data analysis.
  
  
• Teaching experience in undergraduate or graduate level coursework in STEM required.

• Demonstrated experience/knowledge of Statistics and Machine Learning from both theoretical and applied perspectives.
• Experience in developing a curriculum or providing training in a client-facing endeavor.
• A good sense of the relevance of academic data science to industrial applications.

• Forward thinking with a strong growth mentality, i.e. constantly strengthening yourself on all fronts relevant to the growth of our school.
• Passionate about teaching and helping your students succeed in their careers.
• A team player who can multitask if necessary and can step up to new challenges in a growing company.

Perks

• Competitive salary, adjustable hours, and flexible vacation policy.
• Benefits include 401k retirement plan and medical, dental, vision insurances.
• Opportunity to train, research, and learn in the field of data science on-the-job; a chance to interact with active data science communities through conferences, Meetup events, etc.
• Completely stocked snack pantry.
• High-quality computational equipment.