Welcome to Behind the Model — where we spotlight the people who are building the future of finance at Model ML. Get to know their stories, journeys, and what drives them. Interested in joining the team? Explore our openings here.
Ahmed grew up in Karachi and has lived in nine cities across five countries. He started on the trading floor at Fidelity as a technologist, then moved back home and ran a K-12 school serving 600 students.
During his MBA at Cambridge, he fed a dozen documents into Model ML for a research project and was hooked by the quality of the outputs. Three months later, he joined the team, ready to pick up anything.
Today, Ahmed focuses on translating PE and IB workflows into product, onboarding large client teams, and proving adoption with clear metrics. To him, the draw of Model ML was straightforward: work with sharp people, ship quickly, and change how investors research, diligence, and communicate decisions.
What do you enjoy the most about working at Model ML?
The pace. Every week feels like building the future in real time.
What’s your favourite use case?
Deal-screening workflow: Comps and a first-draft IC memo in under 5 minutes, with Human-in-the-Loop. It takes what used to be a week of analyst work (chasing filings, pulling peer sets, formatting tables, drafting memos) and compresses it into minutes. The analyst still controls the output, but the baseline is already built. That shift changes how fast teams can triage deals and redirect capacity to higher-value work.
What’s your favourite AI tool?
Notion. It’s brilliant at imposing structure on unstructured work. I use it to organise training programs, client workflows, and internal processes so nothing falls through the cracks. The pace of innovation is also impressive. Every release feels like a real upgrade, not a gimmick.
Describe your job in five emojis or less.
🤖🤖🤖🤖🤖
Welcome to Behind the Model — where we spotlight the people who are building the future of finance at Model ML. Get to know their stories, journeys, and what drives them. Interested in joining the team? Explore our openings here.
Ahmed grew up in Karachi and has lived in nine cities across five countries. He started on the trading floor at Fidelity as a technologist, then moved back home and ran a K-12 school serving 600 students.
During his MBA at Cambridge, he fed a dozen documents into Model ML for a research project and was hooked by the quality of the outputs. Three months later, he joined the team, ready to pick up anything.
Today, Ahmed focuses on translating PE and IB workflows into product, onboarding large client teams, and proving adoption with clear metrics. To him, the draw of Model ML was straightforward: work with sharp people, ship quickly, and change how investors research, diligence, and communicate decisions.
What do you enjoy the most about working at Model ML?
The pace. Every week feels like building the future in real time.
What’s your favourite use case?
Deal-screening workflow: Comps and a first-draft IC memo in under 5 minutes, with Human-in-the-Loop. It takes what used to be a week of analyst work (chasing filings, pulling peer sets, formatting tables, drafting memos) and compresses it into minutes. The analyst still controls the output, but the baseline is already built. That shift changes how fast teams can triage deals and redirect capacity to higher-value work.
What’s your favourite AI tool?
Notion. It’s brilliant at imposing structure on unstructured work. I use it to organise training programs, client workflows, and internal processes so nothing falls through the cracks. The pace of innovation is also impressive. Every release feels like a real upgrade, not a gimmick.
Describe your job in five emojis or less.
🤖🤖🤖🤖🤖
Welcome to Behind the Model — where we spotlight the people who are building the future of finance at Model ML. Get to know their stories, journeys, and what drives them. Interested in joining the team? Explore our openings here.
Ahmed grew up in Karachi and has lived in nine cities across five countries. He started on the trading floor at Fidelity as a technologist, then moved back home and ran a K-12 school serving 600 students.
During his MBA at Cambridge, he fed a dozen documents into Model ML for a research project and was hooked by the quality of the outputs. Three months later, he joined the team, ready to pick up anything.
Today, Ahmed focuses on translating PE and IB workflows into product, onboarding large client teams, and proving adoption with clear metrics. To him, the draw of Model ML was straightforward: work with sharp people, ship quickly, and change how investors research, diligence, and communicate decisions.
What do you enjoy the most about working at Model ML?
The pace. Every week feels like building the future in real time.
What’s your favourite use case?
Deal-screening workflow: Comps and a first-draft IC memo in under 5 minutes, with Human-in-the-Loop. It takes what used to be a week of analyst work (chasing filings, pulling peer sets, formatting tables, drafting memos) and compresses it into minutes. The analyst still controls the output, but the baseline is already built. That shift changes how fast teams can triage deals and redirect capacity to higher-value work.
What’s your favourite AI tool?
Notion. It’s brilliant at imposing structure on unstructured work. I use it to organise training programs, client workflows, and internal processes so nothing falls through the cracks. The pace of innovation is also impressive. Every release feels like a real upgrade, not a gimmick.
Describe your job in five emojis or less.
🤖🤖🤖🤖🤖
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