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.

As an economics honors student who tutors math through the calculus level, Davis lives in the exact overlap where business calculus sits — applying derivatives and integrals to problems like profit maximization and marginal analysis that he encounters in his own coursework. That dual fluency means he can walk through a cost function optimization and explain both the calculus mechanics and the economic reasoning behind the result.

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.

I love helping students in topics related to math, to finance (public and private equity) and to engineering. I believe that if I can't explain concept, then I don't understand it. By that same token, if a student can't explain a concept back to me, then they don't understand it even if they say they do. I believe in getting to know all students, as their background is intricately connected with how they learn.

Three engineering degrees — including one in applied mathematics — mean Rahi has worked through calculus from every angle, pure and applied. For business calculus students, he zeroes in on translating derivative and integral mechanics into the language of profit maximization, cost analysis, and demand elasticity, bridging the gap between the math they're learning and the business decisions it models.

Where most business calculus students stumble isn't the differentiation itself — it's translating a word problem about profit margins or demand curves into the right function to differentiate. Jhonatan's biology and neuroscience training gave him years of practice applying calculus to real systems, from modeling population growth to analyzing rates of change in physiological data. That applied mindset, rated 5.0 by students, carries directly into breaking down optimization and marginal analysis problems.

Most business calculus students aren't struggling with the mechanics of taking a derivative — they're struggling to connect that derivative to what's actually happening with cost, revenue, or demand. David's background spanning computer science, history, and graduate work at Columbia and Chicago trained him to translate between abstract frameworks and applied contexts, which is exactly the skill business calc requires. Rated 4.9 by students.

Most business calculus students don't struggle with the mechanics of differentiation — they struggle with translating a word problem about profit margins or demand curves into the right equation to solve. Professor Florence's applied math degree from UCLA and PhD-level engineering work mean she's spent years moving between abstract formulas and real-world modeling, which is exactly the skill business calc demands. She teaches students to read an optimization problem the way a business analyst would, then execute the calculus cleanly.

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.

As an economics honors student who tutors math through the calculus level, Davis lives in the exact overlap where business calculus sits — applying derivatives and integrals to problems like profit maximization and marginal analysis that he encounters in his own coursework. That dual fluency means he can walk through a cost function optimization and explain both the calculus mechanics and the economic reasoning behind the result.

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.

I love helping students in topics related to math, to finance (public and private equity) and to engineering. I believe that if I can't explain concept, then I don't understand it. By that same token, if a student can't explain a concept back to me, then they don't understand it even if they say they do. I believe in getting to know all students, as their background is intricately connected with how they learn.

Three engineering degrees — including one in applied mathematics — mean Rahi has worked through calculus from every angle, pure and applied. For business calculus students, he zeroes in on translating derivative and integral mechanics into the language of profit maximization, cost analysis, and demand elasticity, bridging the gap between the math they're learning and the business decisions it models.

Where most business calculus students stumble isn't the differentiation itself — it's translating a word problem about profit margins or demand curves into the right function to differentiate. Jhonatan's biology and neuroscience training gave him years of practice applying calculus to real systems, from modeling population growth to analyzing rates of change in physiological data. That applied mindset, rated 5.0 by students, carries directly into breaking down optimization and marginal analysis problems.

Most business calculus students aren't struggling with the mechanics of taking a derivative — they're struggling to connect that derivative to what's actually happening with cost, revenue, or demand. David's background spanning computer science, history, and graduate work at Columbia and Chicago trained him to translate between abstract frameworks and applied contexts, which is exactly the skill business calc requires. Rated 4.9 by students.

Most business calculus students don't struggle with the mechanics of differentiation — they struggle with translating a word problem about profit margins or demand curves into the right equation to solve. Professor Florence's applied math degree from UCLA and PhD-level engineering work mean she's spent years moving between abstract formulas and real-world modeling, which is exactly the skill business calc demands. She teaches students to read an optimization problem the way a business analyst would, then execute the calculus cleanly.