About Aptura AI
Aptura AI builds domain-specific AI systems for regulated industries such as finance by combining frontier models with real-world expert judgment. Our leadership includes professionals from Lazard and Partners Group, and we operate across London and San Francisco. We work with AI labs and vertical AI companies to improve how models reason in finance, healthcare, and legal workflows.
The opportunity
This fellowship is designed for candidates who want to apply serious finance training to frontier AI systems.
You will work at the intersection of:
· Corporate finance and investment analysis
· Financial modeling and valuation
· AI system evaluation and model behavior
What you will do
You will work directly with Aptura's founders, finance practitioners, and ML teams on projects that shape how advanced AI systems perform on real financial tasks. Typical work includes:
Build and validate real world financial models and tasks: Develop DCFs, comparable company analyses, precedent transaction analyses, LBO cases, and credit assessments used as expert reference cases and evaluation benchmarks for AI systems.
Analyze financial reasoning quality: Review model-generated outputs and identify errors in logic, assumptions, methodology, or market interpretation that a trained analyst would catch.
Design decision frameworks: Translate how finance professionals think through trade-offs, uncertainty, and scenario analysis into structured frameworks that can be used to test model performance.
Create high-signal evaluation tasks: Help define finance problems that differentiate strong model reasoning from weak model reasoning across topics such as M&A, debt structuring, earnings analysis, and capital allocation.
Run human-versus-model comparisons: Compare AI analyses against practitioner approaches to isolate where the model is missing context, using weak assumptions, or drawing unsupported conclusions.
Collaborate with research and ML teams: Work cross-functionally to refine prompts, improve task design, and increase the reliability of finance-specific model behavior.
Above all, we're a lean and fast-moving team - while the above captures the core of the role, we're looking for adaptable, enthusiastic candidates who want to contribute to growing the business in whatever way they can.
Why this experience is valuable
Direct exposure to how frontier AI systems are evaluated in finance.
First-hand insight into how quickly AI is reshaping finance, ranging from research and valuation support to credit analysis, diligence, and investment decision workflows.
Hands-on experience spotting and explaining reasoning failures in model outputs.
Practical insight into AI-enabled workflows relevant to investment banking, private equity, credit, and equity research roles.
A strong narrative for candidates interested in the future of finance and AI-augmented decision making.
Who You Are
Currently enrolled or recently graduated from a finance master's or advanced graduate programme (MFin, MBA, MSc Finance, or equivalent).
Minimum 3-5 years of full-time experience in Investment Banking / M&A, Private Equity, Equity Research, Credit & Leveraged Finance, or Corporate Finance.
Confident in financial statement analysis, valuation methodologies (DCF, comps, precedents, LBO), etc.
Clear communication and the ability to explain complex financial logic in structured steps.
Detail-oriented: you spot the errors that others miss.
High attention to detail and comfort reviewing work critically.
A genuine interest in how AI systems will change finance workflows.
Bonus: CFA Level I or above, or equivalent evidence of strong technical finance training.
Fellowship Details
Duration: 4-12 weeks (project-based)
Commitment: 20–40 hours/week, flexible scheduling
Location: Remote
Compensation: Hourly pay dependent on experience
Start date: Immediate/rolling
