Tomorrow’s Quants: what it takes to be a next-gen modeller

Employers increasingly prize mix of hard and soft skills, Risk.net survey reveals

Key points Summary Q&A

• A new Risk.net survey will show the market for junior quants is evolving, with new and sometimes surprising skills becoming essential attributes for candidates.
• Tomorrow’s Quants, a survey of 39 senior hiring quants, highlights the importance of people skills in junior roles, with 98% of respondents agreeing on these as a necessity.
• At the same time, only three firms expect graduates to spend over 50% of their time on AI-related projects, and across other institutions this number is an average 20%.
• Alongside these insights into career and educational pathways, the project will produce a companion podcast series of senior quant interviews, as well as the Risk.net global rankings of top quant finance programmes.

These summaries are generated by an LLM, but edited by humans.

There was a time – not that long ago – when maths skills were the skeleton key to almost any quant role in finance. Those skills remain important, but many employers are now also seeking non-technical know-how that undermines a stereotype: quants who can code but can also communicate.

This is just one of the trends revealed by a Risk.net survey of the job market for aspiring quants. 

A total of 39 employers participated: 19 head quants from large banks, including 10 global systemically important banks; 14 large asset managers, hedge funds and market-makers; and half a dozen prominent data and financial software vendors.

98%

of respondents view people skills as important across all quant roles

The outcome is an editorial project – Tomorrow’s Quants – that will be published in three parts during November and December. In the first segment, we ask senior quants – those responsible for hiring and developing the next generation – to share their recruitment criteria, the results of which will be presented across two articles.

The survey spans questions about the required knowledge of candidates in technical subjects: from stochastic calculus to pricing models; from portfolio theory to coding proficiency in various programming languages.

Some findings will not raise eyebrows: coding in at least one language is a core requirement for most recruiters, for example. But among the findings that may surprise is the increasing demand for soft skills. Almost all respondents view people skills as important across all quant roles, while collaboration, curiosity and creativity were deemed the most desired traits across a range of disciplines. 

The ability to present a research project emerges as a key skill – ‘very important’  for 74% of the responding institutions – and ‘somewhat important’ for the remainder. Firms require their employees to communicate effectively with clients and senior management, work well with other teams and convey key model information to successors. The transfer of knowledge is often a challenge: individuals who can navigate these situations well are highly regarded.

Similarly, the capacity to write clearly is one almost all  respondents consider advantageous. 

But employers may also have revealed a collective blind spot – while they want their hires to be comfortable interacting with both management and clients, they apparently don’t place much value on being likeable. As a requirement, charisma was universally ranked last.

Only three respondents – ones that represent firms where AI is central – expect graduates to spend more than 50% of their time on AI-related projects

As well as desirable personality traits, respondents were asked to identify their top red flags. Here, the most commonly cited traits were overconfidence and arrogance – an inability to admit mistakes – along with intellectual and learning gaps.

Another set of questions focuses on education, exploring which academic paths best equip candidates with the necessary skills for specific roles. Some employers have partnerships with universities that range from informal preferential recruitment routes to the establishment of joint labs, where young researchers can experience both an academic and an industry environment. The results show these collaborations are highly valued by both parties, and are greatly appreciated by students, who benefit from the combined experience of being researchers and desk quants.

One data point Risk.net will explore in the forthcoming articles is that only three respondents expect graduates to spend more than 50% of their time on AI-related projects (these respondents are the ones representing firms at which AI is central to their business, including one that makes AI-only predictions). The average of this figure for all other financial institutions is close to 20% – perhaps surprisingly low.

Quants wanted

The second segment of the project is the Quantcast Master’s Series, comprising six podcasts featuring directors of master’s programmes in quantitative finance. Selected programmes from four countries – Australia, Switzerland, the UK, and US – showcase different structures, durations and philosophies, allowing listeners to hear directly from educators on how they organise their programmes and adapt to local market demands.

These conversations identify a shift in applicant behaviour, with fewer candidates from India and China now trying to go to the US, and more targeting Europe and Australia. Global mobility is a recurring theme of the survey: 60% of respondents to the report at least half of their graduate intake or junior quants require visa sponsorship, with 12% of this group indicating that all of their juniors require visas.

Related

Quant Finance Master’s Guide 2025 

Risk.net’s guide to the world’s leading quant master’s programmes, with the top 25 schools ranked

Collectively, the directors discuss the differences between financial engineering schools, quant finance courses and business schools. Although the distinctions between these types of programmes are often blurred, a common characterisation is that business schools focus on model implementation, while master’s programmes in quantitative finance provide a strong theoretical foundation, and financial engineering courses strive to balance both aspects.

The final component of the project is the 2026 edition of the Quant Finance Master’s Guide and Ranking. The eighth edition of the guide collects information from administrators of master’s programmes, offering readers a comprehensive view of the educational landscape.

With the collected data, Risk.net will compile its annual ranking of the top programmes globally – a hierarchy that for the past two editions has been led by Baruch College of the City University of New York. Ranking criteria include placement rates, average salaries of graduates, programme selectivity, and lecturer statistics. A detailed methodology will accompany the guide and ranking.

As a whole, the Tomorrow's Quants project is a resource for junior candidates interested in a career in quantitative finance – comparing available programmes worldwide and exploring the skills they will need to launch their careers. We hope it also proves useful to master’s programme directors – offering insights into the relative evolution of their peers and of the shifting demand for skills – and to employers that are seeking to stand out in an intensely competitive market for talent.

Editing by Duncan Wood and Louise Marshall