My startup just had an angel round and we basically want to spend it on a critical hire. I’m torn on what it is. We’ve built a unique, gamified intelligent tutoring system, essentially a video game for learning the MCAT. Our platform is an intelligent tutoring system which diagnoses student weaknesses, assigns them content and videos in fun games, and then uses AI to tutor them on topics they struggle with.
The most fascinating part about our service is that it's built like a sensor network: from the beginning to the end, every interaction with our website is tracked and used to update the model's understanding of student knowledge. Every interaction on our platform is a data point – highlights, answer changes, even the coins they earn. This gives us unprecedented insight into how top performers master complex material. We're capturing the real-time cognitive processes of the highest achievers, not just their scores. We are leveraging insights from behavioral economics to optimize learning through a proprietary coin system – what students prioritize, and how they respond to incentives. For example, we learned that higher-performing students on MCAT CARs reading passages actually highlight less rather than more, turning theory of excellent test-taking into data-driven insights.
We got a lot of traction early on but the market for MCAT prep. 86% of people take the MCAT from March-September. By building a great product now, with amazing data tracking, we can learn a ton from this market peak and gain a critical lead in ITS architecture.
However, does that mean I hire a data engineer or a senior architect? Does that mean I look for an SWE with data experience and solid mathematics chops? Ideally, we’d have an experienced technical dev that can create essential data pipelines/help us run experiments with that data/lead our team of interns/implement machine learning systems/and also have the experience to take a product end-to-end…but it feels like I’m looking for a damn unicorn.
I’ve settled on “Software Engineer, Data & Learning Systems” but I feel like that’s incorrect.
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[ 3.7 ms ] story [ 12.4 ms ] threadMy startup just had an angel round and we basically want to spend it on a critical hire. I’m torn on what it is. We’ve built a unique, gamified intelligent tutoring system, essentially a video game for learning the MCAT. Our platform is an intelligent tutoring system which diagnoses student weaknesses, assigns them content and videos in fun games, and then uses AI to tutor them on topics they struggle with.
The most fascinating part about our service is that it's built like a sensor network: from the beginning to the end, every interaction with our website is tracked and used to update the model's understanding of student knowledge. Every interaction on our platform is a data point – highlights, answer changes, even the coins they earn. This gives us unprecedented insight into how top performers master complex material. We're capturing the real-time cognitive processes of the highest achievers, not just their scores. We are leveraging insights from behavioral economics to optimize learning through a proprietary coin system – what students prioritize, and how they respond to incentives. For example, we learned that higher-performing students on MCAT CARs reading passages actually highlight less rather than more, turning theory of excellent test-taking into data-driven insights.
We got a lot of traction early on but the market for MCAT prep. 86% of people take the MCAT from March-September. By building a great product now, with amazing data tracking, we can learn a ton from this market peak and gain a critical lead in ITS architecture.
However, does that mean I hire a data engineer or a senior architect? Does that mean I look for an SWE with data experience and solid mathematics chops? Ideally, we’d have an experienced technical dev that can create essential data pipelines/help us run experiments with that data/lead our team of interns/implement machine learning systems/and also have the experience to take a product end-to-end…but it feels like I’m looking for a damn unicorn.
I’ve settled on “Software Engineer, Data & Learning Systems” but I feel like that’s incorrect.
Any guidance?