Job Description

Why Grasp

Grasp is an AI platform for the financial advisory industry. The $1.4 trillion financial advisory industry relies heavily on costly and scarce cognitive labor. The industry is so inefficient that advisory firms can charge millions of dollars for teams of junior employees, whose work is 90% manual and repetitive. It is clear that AI will automate large parts of this work and provide a massive uplift in productivity.

Our platform uses the latest advances in AI to solve the time-consuming and complex workflows unique to the financial advisory industry. Since launching our product early 2024, we have grown rapidly to support almost 200 customers across 25 countries, secured backing by top-tier investors, and are now scaling our team quickly in our Stockholm and London offices.

About the role

As a Finance AI Specialist at Grasp, you’ll bridge the world of finance and AI — bringing deep financial understanding to help shape, tune, and validate our products. You’ll work closely with our engineers and product team to ensure that our AI systems meet the precision and rigor expected in high-stakes financial workflows.

You’ll be hands-on — testing the product, labeling data, building evaluation sets, and defining what “good” looks like when AI takes on complex M&A and investment tasks. Your work will directly impact how our models reason about financial statements, valuations, transaction documents, and client deliverables.

Your responsibilities will include:

• Acting as the financial domain expert across the product and engineering teams — ensuring our models and prompts reflect real-world financial reasoning.
• Testing AI outputs for accuracy, relevance, and domain soundness across use cases such as company analysis, valuation, and deal commentary.
• Building and maintaining evaluation datasets and test suites that define quality thresholds for AI-generated work.
• Labeling and curating financial data — from transaction comps to management presentations — to train and fine-tune our models.
• Working with the product and ML teams to translate financial logic (e.g., DCF mechanics, accretion/dilution, purchase price allocation) into measurable evals and structured training data.
• Providing feedback loops that guide model improvements and prompt iteration.
• Helping define quantitative success criteria for AI features before launch.
  

Must-haves

• 2–4 years of experience in investment banking, management consulting, or private equity, ideally with exposure to M&A or commercial due diligence.
• Deep fluency in finance and business fundamentals — company analysis, market sizing, and strategic reasoning.
• Strong attention to detail and ability to evaluate analytical work as if it were a live client deliverable.
• Curiosity and comfort working with AI-driven tools — experience testing, evaluating, or fine-tuning outputs.
• Structured communicator who can write crisp evaluation notes, logic summaries, and feedback for improvement.
• Collaborative mindset — you’ll work daily with engineers and product managers.

Nice-to-haves

• Prior experience labeling, evaluating, or curating data for AI or ML systems.
• Experience in early-stage startups or product environments.
• Understanding of generative AI, LLM prompting, or evaluation methodologies.
• Strong PowerPoint/Excel skills and basic familiarity with Python or SQL.