Associate

We're working with a global valuation and financial advisory firm who are growing their funds Valuation practice. They are hiring an Analyst or Associate into their London office.

This is a quant-flavoured finance role, applying data science principles to valuation problems.

If you have an engineering or hard-science background, strong Python, and enough finance exposure to know you want to go deeper into it, this could be a good fit.

The team provides independent valuations to alternative asset managers and funds, including evergreen funds (SICAVs and their US equivalents) across private credit and private equity, with a heavy concentration in secondaries.

The core of the work is daily valuations on secondaries positions. The team has access to an enormous volume of client data and a real appetite for turning it into new products.

What you'll actually do

• Build, calibrate and run the regression models that drive daily valuations
• Interrogate and understand the data clients send you, and chase down what doesn't look right
• Second-level review of work produced by an offshore team of data scientists
• Support complex financial models for specific fund structures and complex start ups
• Prepare fee proposals, scoping discussions, pitch materials and internal pricing memos
• Pitch to clients, including new products and running proofs of concept
• Partner with the MD to origin new tech-led valuation mandates

Due to the US client base of this business line, you will need to be comfortable working and being available in the later evening UK time - in practice this can mean a later start and finish than a typical 9-5.

What they're looking for

• A STEM degree from a top university, with excellent academics (ideally a 1st or high 2:1. Master's level qualification is also welcome
• 2 to 6 years of experience. Roughly 2+ for Analyst, 4+ for Associate
• Good Python proficiency as well as Excel, and familiarity with VBA and a BI tool such as Power BI or Sigma
• Good working knowledge and practical experience of regression models and applied analytics
• Maturity, ownership and a self-starting streak

Nice to have:

• Financial services or capital markets experience,
• CFA or MBA

Why this role is worth a conversation

• The client list is the top tier of secondaries investors, and it is growing fast
• You'll learn valuation properly, using the analytical toolkit you already have, rather than starting from scratch
• You'll be building the automation and LLM tooling
• Two or three years here gives you a combination of quantitative skill, AI fluency and private markets knowledge that very few people have
• The valuation work will cover some of the most talked-about private companies in the world