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On that early morning in June 2012, his compiler crunching out machine code in one window, his forlorn dating profile sitting idle in the other, it dawned on him that he was doing it wrong.
He'd been approaching online matchmaking like any other user.
He could match every woman in LA who might be right for him, and none that weren't.
Chris Mc Kinlay used Python scripts to riffle through hundreds of Ok Cupid survey questions.
He'd sent dozens of cutesy introductory messages to women touted as potential matches by Ok Cupid's algorithms.
The script would search his target demographic (heterosexual and bisexual women between the ages of 25 and 45), visit their pages, and scrape their profiles for every scrap of available information: ethnicity, height, smoker or nonsmoker, astrological sign—“all that crap," he says.
The experience kindled his interest in applied math, ultimately inspiring him to earn a master's and then a Ph D in the field.
"They were capable of using mathematics in lots of different situations," he says.
(The subject: large-scale data processing and parallel numerical methods.) While the computer chugged, he clicked open a second window to check his Ok Cupid inbox.
Mc Kinlay, a lanky 35-year-old with tousled hair, was one of about 40 million Americans looking for romance through websites like Match.com, J-Date, and e-Harmony, and he'd been searching in vain since his last breakup nine months earlier.