Our conversation with Ozge Yeloglu, Lead Data Scientist, Microsoft Canada.
Ozge Yeloglu has had to work hard to get to where she is today.
From a young age in Turkey, she had a keen interest in computers, despite not having access to one at home.
But that didn’t stop her from following her passion.
In 1999, when she began her computer science degree, she still didn’t own a computer (or even know what a floppy disk was), but she persevered.
As an undergraduate, she struggled to find an outlet for her love of programming and computing technology, but a pivotal moment came in 2004 when a professor handed her a book on neural networks.
That single gesture started Ozge on a journey that would eventually see her leading the data and AI teams for one of biggest players in Canadian technology.
The Road To AI Leadership
After studying for her advanced degree at Dalhousie University in Halifax, she made the jump into #startuplife with a fellow PhD candidate.
Three years of incredibly hard work as a tech co-founder followed but unfortunately things ended the way of so many new ventures.
But the path of learning and advancing computer science continued.
In 2016, Ozge was hired as the first data scientist at Microsoft Canada with a focus on building analytics solutions for some of the biggest financial services companies in the country.
In just over two years, she has expanded the team to 11 members and continues to work on changing the technology landscape for enterprise customers, while being the voice of AI at Microsoft Canada.
Tune in to this episode as host Jaxson Khan (Nudge AI) learns more about Ozge’s fascinating journey and her unique perspectives on artificial intelligence.
What You’ll Hear
- The power of women in tech groups and mentor-ships
- The loneliness of the PhD candidate 😉
- Why it might be a bit too early to worry about a technology skills gap in Canada.
- Why chatbots and intelligent agents represent design and UX issues, rather than NLP or ML challenges
- Why Ozge feels that everything that can be automated should be automated, starting with vacuum cleaners.
- Can (or should) we clean historical data to remove bias? Or should we train AI to detect it?
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Host: Jaxson Khan
Senior Producer: Mike Letourneau
Assistant Producer: Francois Desmarais
Executive Producer: Chris McLellan
Episode Sponsor: Electric Brain
Chatbot Sponsor: Ada
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