As an MCAT Prep Instructor, you will support students in and out of class, helping them develop critical thinking skills across the sciences. You will also utilize data to help close the opportunity gap for underrepresented students.
MCAT Prep Instructor - University of Denver
Join Kaplan’s growing community of test-prep experts as a part-time, hybrid MCAT Instructor!
Our teachers enjoy competitive pay and a flexible, hybrid schedule while helping students realize their potential.
We take the pain out of planning and prepping by providing our teachers with a suite of learning-science backed resources, prepared curriculum, and score-boosting strategies.
This opportunity is a great fit for current medical students, students who have had success on the MCAT, those taking a gap year or deferred admission, or those just interested in lifelong education and making a difference in the lives of other students.
As a MCAT Teacher, you’ll: - Enjoy a flexible, hybrid, part-time teaching schedule, as most courses take place on weekends and/or evenings - Support students both in and out of class, enabling them to solve problems with critical thinking across the sciences - Use data to close the opportunity gap for underrepresented students - Connect with colleagues remotely while completing training and class prep from the comfort and convenience of home Benefits include: - Competitive hourly teaching rates starting at $35-50/hr based on credentials and geographic location - Flexible schedule of mixed in-person teaching sessions and remote prep work - Paid comprehensive training and lesson preparation - Continual learning, coaching, and mentoring opportunities - Access to Health and Welfare Plans - 401K plan - Commuter Benefits Program - Free or discounted classes for you and/or immediate family members - Employee Discounts including travel, local deals, and health and wellness offers Candidates must: - Have scores within the 90th percentile of the LSAT - Be authorized to work in the U.S.
Location: Denver, CO, USA
Business Unit: 00073 Kaplan Grad
Kaplan is committed to cultivating an inclusive workplace that values diversity, promotes equity, and integrates inclusivity into all aspects of our operations. We are an equal opportunity employer and all qualified applicants will receive consideration for employment regardless of age, race, creed, color, national origin, ancestry, marital status, sexual orientation, gender identity or expression, disability, veteran status, nationality, or sex. We believe that diversity strengthens our organization, fuels innovation, and improves our ability to serve our students, customers, and communities. Learn more about our culture here [https://kaplan.com/work-with-us/our-culture/].
Kaplan considers qualified applicants for employment even if applicants have an arrest or conviction in their background check records. Kaplan complies with related background check regulations, including but not limited to, the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. There are various positions where certain convictions may disqualify applicants, such as those positions requiring interaction with minors, financial records, or other sensitive and/or confidential information.
Kaplan is a drug-free workplace and complies with applicable laws.
Candidates must commit to a minimum of 8 months and work at least 10 hours per week. Additionally, applicants should have scored within the 90th percentile of the MCAT and be authorized to work in the U.S.
Market context
MCAT prep roles in Colorado are typically competitive because employers look for strong test performance, reliable long-term availability, and the ability to teach consistently alongside other commitments. This position requires at least 8 months of commitment, a minimum of 10 hours per week, and MCAT scores in the 90th percentile, so applicants should confirm their schedule and work authorization before applying. The job requirements and benefits here are AI-summarized from the original posting, which can save candidates time when comparing fit.