Pre-College Instructor, Data Science (On-Campus), Summer 2025
New York, NY, United States
Company Description
Columbia University's Pre-College Programs offer high-achieving high school students the opportunity to engage in exploratory coursework at the college level, studying alongside peers from around the world. This highly selective program is open to students entering grades 9 and through the summer after their senior year.
Job Description
Columbia University’s Pre-College Programs for High School Students is seeking qualified candidates to develop and teach on-campus courses during Summer ’25.
Reporting to the Senior Director of Instruction and Curriculum for Pre-College Programs, Pre-College Instructors develop and deliver immersive non-credit courses for high-achieving high school students. They guide and supervise students when classes are in session, and write a holistic evaluation of each course participant after classes conclude. For more information on the program–including course sessions and times–please see here.
Course Descriptions
Data Science and Machine Learning 1
Data science and machine learning are exciting and popular disciplines. While different fields, they work best in sync to help change the way humans think, behave, and interact. In fact, some of the most popular data science methods stem from machine learning. Through this course, students will be introduced to the foundations of both science areas and explore available career opportunities. Beginning with an overview of the landscape and real-world applications, students will learn how data science and machine learning impact the world in which we live, every day. Further, students will gain hands-on experience with introductory coding using Python and become versed in popular machine learning algorithms. By the end of the course, students will use their benchmark knowledge to analyze and present data ethically and effectively. Finally, students will leave the course prepared for more advanced practice in data science and machine learning.
Note: This course is for students with little-to-no previous experience with coding/programming. Students with more advanced knowledge should consider Data Science and Machine Learning 2.
Data Science and Machine Learning 2
The power of data science and machine learning can change the world. From voice activation to video game programming to advancements in medical science - the possibilities for activation are endless. Through this advanced course, students will leverage their foundational knowledge of Python to develop a more sophisticated programming skill set. Further, students will use a variety of mathematical techniques (statistics, linear algebra, and probability) to analyze data and create impactful visualizations. By course completion, students will become well-versed in a range of strategies and techniques in both data science and machine learning and become data-driven decision makers. Further, students will be able to apply communication skills and fairness frameworks to identified solutions, making them invaluable assets to any future data science/machine learning classroom, or future employer.
Note: This course is for students with prior programming experience (in particular, Python) and/or previous coursework in Data Science and Machine Learning. Further, some background in statistics and linear algebra is helpful. Students with little-to-no prior experience in these areas should explore our Data Science and Machine Learning I course.
Course Schedules
Data Science and Machine Learning 1
Summer A: June 30th to July 18th
Summer B: July 22nd to August 8th
- 9:10am - 11:00am & 1:10 - 3:00pm EST -OR-
- 11:10am-1:00pm & 3:10pm- 5:00pm EST
Data Science and Machine Learning 2
Summer B: July 22nd to August 8th
- 9:10am - 11:00am & 1:10 - 3:00pm EST -OR-
- 11:10am-1:00pm & 3:10pm- 5:00pm EST
Please Note: Course(s) and course availability is subject to change. Dates and class times are tentative and subject to change.
Responsibilities
- Develop course content, syllabus, lesson plans, and assigned work, in accordance with Pre-College templates and regulations
- Lead and attend all class sessions, including escorting students to and from campus for field trips
- Establish and maintain a dynamic in-class environment tailored for our high school population
- Evaluate student work and write a holistic evaluation of each participant after the course ends
- Monitor and address student concerns and inquiries (you will have around 20-24 students)
- Attend and complete all required online trainings
Qualifications
- Graduate degree or equivalent professional or academic background
- Expertise in the pertinent subject matter
- Aptitude for teaching
Additional Information
Hiring Salary
- Summer B (On-Campus): $7,000 - $9,000
- A one-time course development fee will be paid to first time instructors. Development fee rates are $1,500 for 3-week courses and $750 for all other courses.
Other Requirements
- Please specify the course (either Data Science and Machine Learning 1 or Data Science and Machine Learning 2) and session(s) you would be interested in teaching in the Message to the Hiring Team field
- Please submit a resume inclusive of teaching experience as well as formal teaching evaluations (if available)
- Applicants must have U.S. work authorization and will need to be in the U.S. while teaching. Employment eligibility is contingent upon valid work authorization. Individuals on STEM OPT or holders of the following visa types are ineligible to teach Pre-College: B-1, E-3, H-1B, J-1, and O-1.
- Applicants may not hold a concurrent appointment with Columbia for the duration of their appointment
- Once hired, applicants are required to submit to a third party background check and complete Protection of Minors training in addition to other training(s) mandated by the University and Pre-College Program
All your information will be kept confidential according to EEO guidelines.
Columbia University is an Equal Opportunity/Affirmative Action employer.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Linear algebra Machine Learning Python Statistics STEM Teaching
Perks/benefits: Career development Medical leave
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