Alejandra Quintos

Alejandra Quintos always liked math. As a young person in Mexico, however, she didn’t know any mathematicians or receive encouragement to pursue a degree in this field. She earned her undergraduate degree in actuarial science, hoping it would open doors to a career in the U.S. During a summer research opportunity at Cornell, mathematics professor Steven Strogatz encouraged her to pursue a Ph.D. in the U.S., and she went on to earn her doctorate in statistics from Columbia.

Quintos applies her training in probability and theoretical statistics to solve problems in finance. One of her interests is microlending, where banks provide loans to small groups of low-income borrowers with no credit history. Through mathematical modeling, she confirmed an ideal group size of five people for microloan repayment. She is using reinforcement learning to glean new insights from microlending data, helping financial institutions optimize loan amounts and set fair interest rates.

Teaching and transmitting knowledge are what Quintos loves about her work. She values communicating with both students and lay audiences, and she relishes moments of insight when her students understand something complicated or see a problem in a new way.

“UW-Madison’s data science degree programs are successful because we are using math for a purpose. Data science specifically has in the background all these mathematical ideas and models that help you make a conclusion about data. Students might not be aware of all the models they are using, but they are there, under the hood.”