to become a leader in AI, Ozge Yeloglu first had to figure out how to believe in herself –

to become a leader in AI, Ozge Yeloglu first had to figure out how to believe in herself

I had to learn the business side of things. A data scientist with generic data science knowledge is not that useful if one doesn’t have the business context. I was working with our sales teams, getting to know our customers and their needs. It was great to be working with people so closely, like I’d done as CEO of my own company.

Two years into the role, I started getting curious about doing more. I told my manager that if there was an opportunity to grow the team, I’d love to be a manager. The position didn’t exist at the time, but in six months, they asked if I wanted to apply for a new role they were creating. I applied, and I’ve been managing a team of 11 people for the past six months.

I had so much to learn because I’d never been a manager at Microsoft before. But I had to push myself out of my comfort zone if I wanted to do big things. My time as a CEO taught me that adaptability is important, as is being able to learn many things at once. That helps at Microsoft, too—being comfortable with things I don’t know and having the drive to learn and keep growing.

Now I’m managing 11 data architects and data scientists while trying to be the AI voice of our company in Canada. I work with our business and marketing teams to plan and actively engage at our customer and public events, help target the right audience for the events, and bring new programs to our business teams, especially AI and startup programs.

I get to do applied AI, so while we’re not solving problems on an algorithmic AI level, we get to work on changing the AI landscape as it pertains to enterprise customers. This includes not only cultural changes for their businesses, but also the technical changes, especially at a data level, such as how to make the data available to everyone in the company so that we can build these AI solutions with them.

I also do many volunteer activities, such as mentoring AI startups, speaking at conferences and customer events, and being active on social media about AI, specifically on the hashtags #AI4good and #AI4earth.

This role is much the same as I experienced in my CEO days—organized chaos. I’m still able to do many things in my current role while staying as technical as I can. I manage a team, work on growing my team members in their careers, work with our customers at the executive level, hear and help them solve their problems, speak at conferences, work with our internal teams on internal and external AI education, and, of course, make sure that my team is creating business outcomes for our company.

But that doesn’t mean my feelings of inadequacy have been totally eradicated. I’m still learning how to win the war over my negative self-talk. I talk it out in therapy, and I also put sticky notes all around me. I have this sticker at home that says, “Do it badly!” and also “Forgive yourself!” which I heard from a TED Talk. Start working on things sooner rather than later instead of first worrying about how big and terrifying a job is, obsessing, and then putting yourself in a hole that you might not be able to get out of.

Instead, I know the best thing to do is jump in, try to figure it out as early as you can, and most likely make mistakes on the way. However, you acknowledge that you made a mistake, learn from it, and keep moving. Learn. Move on. Repeat.

Now I mentor young girls with the hopes that my story will inspire them. I tell them, just because you might come from less privilege than others or have a steeper learning curve or might have no clue where to insert the floppy disk, those barriers don’t have to disqualify you from a killer career doing what you love.

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