When I was in high school, I remember seeing the joy of my math teachers when they would teach in class. This inspired me to become a high school math teacher. The first step was becoming a peer tutor to my classmates. This lead to tutoring math to college students. Then tutoring students while working as a TA. Then I worked as a data scientist which not only did I understand more how to apply math in the workspace, but also learned how to explain math concepts to coworkers without a strong math background. This helped me to shape my tutoring philosophy to relate to the person being tutored and this opened the door to me teaching high school calculus 1 & calculus 2!

Having studied both economics and computer science at Caltech, Brian thinks about calculus the way business students need to — as a tool for modeling decisions, not as an exercise in proofs. He teaches derivatives through the lens of marginal analysis and optimization problems pulled from actual econ coursework, so concepts like cost minimization and revenue maximization click on the first pass.

Mechanical engineering at Carnegie Mellon meant Ryan spent four years applying calculus to real systems — cost modeling, optimization under constraints, rate-of-change problems with physical and financial stakes. That engineering instinct for asking "what does this derivative actually tell us?" translates directly to business calculus topics like profit maximization and marginal analysis. Rated 4.8 by students.

Engineering graduate work is essentially applied calculus — Ellyn spent years using derivatives and integrals to model real systems, optimize designs, and interpret physical data, which maps directly onto the cost, revenue, and marginal analysis problems in a business calculus course. Her PhD in mechanical engineering means she can unpack why an optimization technique works and show students how to set up the problem from scratch, not just mimic a textbook example. Rated 5.0 by students.

Industrial engineering is essentially optimization under constraints — minimizing cost, maximizing throughput, allocating resources — which means Juan's UF coursework overlaps directly with the core problems business calculus students face. He teaches derivatives and integrals through the lens of real decision-making: where a cost function hits its minimum, how revenue changes at the margin, and what an integral actually tells you about total profit. Rated 4.9 by students.

Most business calculus courses move fast from basic differentiation rules straight into optimization and marginal analysis, leaving students who missed a conceptual step scrambling to catch up. Nikhil's mathematics degree gives him the depth to pinpoint exactly where a gap formed — whether it's setting up a cost function from a word problem or interpreting what a second derivative says about diminishing returns — and rebuild from there. Rated 4.8 by students.

As a data analyst with a finance master's degree, Alexandra lives in the applied math that business calculus actually tests — she uses derivatives and optimization models daily to analyze costs, revenue trends, and financial projections. That real-world fluency means she can unpack a profit-maximization problem or an exponential growth function by tying the calculus directly to the business logic behind it, not just the mechanics of solving it.

Computational biology graduate work means Levi spends his days building mathematical models from real data — the same skill business calculus demands when students need to set up a cost function or interpret what a derivative says about profit. His biology-to-data-science path gives him a knack for translating messy word problems into clean calculus steps, which is usually the part that trips business majors up. Rated 4.9 by students.

A PhD in Mathematics and Computer Science means Irene can trace every business calculus concept back to its roots — but more importantly, she knows when not to. She zeros in on the applied side: setting up profit functions, interpreting what a derivative actually tells a manager about changing costs, and using integration to model accumulated revenue. Rated 4.9 by students, she brings decades of teaching experience to a subject where clear, no-nonsense explanation matters most.

Scoring in the 99th percentile on the GMAT quantitative section while working as a cross-border business consultant gave Jing a dual fluency that's hard to find — she handles the calculus and understands the business scenarios it's being applied to. She breaks down optimization and marginal analysis problems by grounding them in real decisions companies face around cost, pricing, and growth. Rated 5.0 by students.

Daniel's dual accounting and finance coursework at UNF means he's already used calculus to solve the exact problems business students encounter — building cost functions from accounting data, then differentiating to find where marginal cost meets marginal revenue. That fluency in both the math and the business language behind it lets him explain not just how to take a derivative, but what the answer actually means on an income statement. Rated 4.9 by students.

A physics degree builds an unusual skill for business calculus: the habit of translating real scenarios into functions and then interpreting what the math actually says. Cory applies that same thinking to cost curves, profit maximization, and demand elasticity — walking students through how to set up the problem from a word-heavy prompt, not just how to differentiate once the equation is already written. Rated 4.9 by students.