An economics major at Brown, Clive spends most of his time building models from data — testing assumptions, isolating variables, and figuring out whether the numbers actually support a conclusion. That process is identical to what science coursework asks students to do, and his 35 ACT confirms he can handle the quantitative and analytical reasoning involved. He's especially useful for students who need to get comfortable reading graphs, interpreting experimental results, and explaining the logic behind their answers.

Studying medical anthropology at Brown means sitting at the intersection of biological science and human behavior, so Katie understands both the content and the reasoning frameworks that science courses demand. She's particularly effective at teaching students how to read experimental setups, interpret data, and connect evidence to conclusions — skills that show up everywhere from biology labs to standardized test passages.

A molecular biophysics major at Brown, Srini lives at the intersection of physics, biology, and chemistry every day. He unpacks scientific concepts — from cellular respiration to Newtonian mechanics to thermodynamics — by tying them back to real phenomena, making the material stick instead of just surviving the next test.

June's science background is unusually broad — she's conducted electrophysiology research on dementia using a mollusk model while also studying physics and engineering at Brown. That combination means she can walk a student through biology's memorization-heavy content one day and tackle force diagrams or circuit problems the next, always tying concepts back to how scientists actually investigate questions in the lab.

Teaching after-school science at Archway Classical Academy means Hasan sees daily which concepts actually trip students up — whether it's confusing mass with weight, misreading a data table, or blanking on how to set up a controlled experiment. His approach leans on the same close-reading instincts he built studying literary arts at Brown: slow down, look at what's actually in front of you, and explain what it means in your own words before jumping to conclusions. Rated 5.0 by students.

Education Studies at Brown required Abby to dig into how people actually learn — including coursework in cognitive development and research design that overlaps heavily with the scientific method. She's especially strong at teaching students to move from observation to explanation, walking them through how to set up a question, test it, and articulate what the results mean. Her 1590 SAT confirms she can handle the quantitative and analytical reasoning science demands.

A Classics major spends a lot of time parsing Latin and Greek roots — the same roots that make up most scientific vocabulary, from "photosynthesis" to "mitochondria" — so Joshua can help students decode terminology that often feels like a foreign language. His 1530 SAT also signals comfort with data interpretation and evidence-based reasoning, two skills that show up constantly in science coursework. Rated 4.7 by students.

A neuroscience degree from Brown means Sophie spent years immersed in biology, chemistry, and data analysis — skills that translate directly to breaking down topics like cell structure, genetics, and the scientific method for younger students. She connects abstract science concepts to how the brain and body actually work, making material click rather than just float on the page.

Ariel tackles elementary and middle school science by connecting abstract concepts — like the difference between physical and chemical changes, or how ecosystems maintain balance — to experiments and real-world examples students can picture. Her psychology training also means she reads frustration and confusion quickly, adjusting explanations before a student shuts down. Rated 5.0 by students.

While science isn't Anna's primary concentration, her analytical approach to learning and her experience tutoring across subjects make her a strong fit for students who need support connecting scientific concepts to reading-heavy assignments like lab reports and research summaries. She's particularly effective at teaching students how to extract key information from dense textbook passages and diagrams.

Three years in a UPenn research lab gave Kahini hands-on experience with experimental design, data analysis, and the scientific method before she moved into her Columbia neuroscience PhD. She teaches science as a way of asking questions — forming hypotheses, interpreting results, and understanding why an experiment is set up the way it is.

An engineering background means Geraldine learned science by applying it — calculating forces, analyzing circuits, interpreting lab data. She brings that applied mindset to tutoring, connecting abstract scientific concepts to tangible problems so students understand the 'why' behind formulas and processes.