Audrey Folaranmi, Data Science Intern, Adobe
Audrey Folaranmi (MIMS ’25) spent the summer as a Data Science Intern at Adobe.
Describe a typical day at your internship.
Typically, I’d tap my badge, exchange a few friendly nods with colleagues, and head to the break room on the 9th floor for a granola bar and my go-to French vanilla latte before settling in at my desk. With my coffee in hand, I’d read through emails and Slack to catch up on anything urgent and map out the tasks for the day. About 20% of my time was spent meeting with stakeholders and my mentor to discuss findings and blockers. I always set aside time for uninterrupted coding or brainstorming sessions. Afterward, I’d grab lunch with my friends at the cafeteria. My go-to used to be sandwiches, but after some playful trolling from my friends, I switched things up with Indian cuisine or the salad bar.
Once lunch was done, I’d dive into debugging code or running data analysis. It often involved troubleshooting errors or optimizing models to ensure everything ran smoothly. If I hit a mental block or felt a bit of brain fog, I’d take a quick break to play pool or basketball to reset. After wrapping up my remaining work for the day, I’d head to the office’s fitness center for a workout before clocking out.
What was the most valuable thing you learned at your internship?
I realized that your personality and the relationships you build are just as crucial as your technical skills. It’s important to network with people beyond your immediate team and genuinely learn about their work and personal interests. These connections broaden your perspective and make you a more well-rounded collaborator. Having access to both current and future leaders in one place is a rare opportunity, and it’s essential to take advantage of that to grow and build lasting relationships. It’s not just about what you know—it’s also about how you engage with others.
What was the biggest challenge?
Stakeholder management was one of the more challenging aspects of my internship. As an intern, you’re still learning the landscape while trying to meet expectations. Balancing stakeholders’ different priorities and communication styles — whether they were managers, engineers, or product owners — required a lot of active listening and adaptability. It was a fine line between providing progress updates and understanding when to push back on certain requests to keep the project on track.
How did your work at the I School prepare you for this role?
The I School provided a solid foundation, especially through coding courses like INFO 206A: Introduction to Programming and Computation; 206B: Introduction to Data Structures and Analytics; and Info 251: Applied Machine Learning. These classes taught me how to approach complex problems with a structured mindset, write efficient code, and use data effectively to drive insights. I could apply those technical skills directly to analyzing datasets and developing algorithms.
Any advice for first-year MIMS students as they prepare for their internships?
Don’t deny yourself opportunities because you think you’re not perfectly qualified. Imposter syndrome can be real but remember that many skills can be learned on the job. Focus on finding roles that align with your interests and tailor your resume to highlight the transferable skills that make you a good fit. Once you’re in the role, stay curious and keep learning — the best growth happens when you’re on the job.
Did your internship influence your career plans after graduation?
Absolutely! Collaborating with various teams gave me insight into roles like machine learning engineering and data engineering, which helped shape my decision to focus on data science for product and strategy development, with plans to pivot into engineering later in my career.
