Beyond the Bonus

Systematic quant finance is one of the few labour markets where compensation is both high and unusually uniform. That combination has consequences. When every serious firm pays “enough,” the relevant questions shift away from headline numbers and towards the architecture underneath: how impact is measured, how behaviour is shaped, and how firms use compensation systems to encode their philosophy.

How much do systematic quats actually make? 

The entry ticket for systematic quant research is a pay package that sits well above most software and banking roles. But within that, the structure of remuneration, not just its absolute level is where incentives live or die. Across hedge funds and prop shops, US quant researcher salaries (base only) cluster around $175-225K at reputable firms, with total compensation around the $300-600K range for early-mid career researchers. At the upper end, experienced researchers and senior individual contributors can earn significantly more, with total compensation stepping into the seven-figure range in strong performance years. 

What’s striking is not just the absolute levels, but the consistency: the market for systematic talent has become so efficient that firms bidding for the same narrow pool of mathematically elite researchers now offer almost indistinguishable compensation bands. A newly minted PhD choosing between a leading prop shop, a quant hedge fund, or even certain high-end trading groups at tech firms often sees remarkably similar headline numbers. In other words, cash has become the baseline, not the differentiator. The arms race has already been priced in; what’s left are the subtler, structural levers of compensation: how bonuses are determined, how research impact is attributed, how capital is allocated, how long-term incentives work, and how geography compresses or inflates pay.

How is remuneration actually structured?

While base salaries get most of the attention, quant compensation is less about pure payouts and more about the architecture of incentives: how a firm recognises research impact, allocates resources, and balances collaboration with individual contribution.

In practice, systematic firms use a mix of structures that reflect their investment philosophy, risk appetite, organizational design, and thirst for intellectual retention. 

As previously mentioned, base salaries continue to be a strong recruitment tool and are deliberately generous across major firms, often starting at a $175-250K range, giving a sense of stability to junior quants whose year-to-year P&L exposure can fluctuate. For early-career researchers, this high fixed floor reduces the perceived risk of entering an industry with inherently volatile outcomes. 

Most firms describe bonuses as ‘’discretionary", but in reality, they are guided by multiple layers, often blurry ones, of attribution, including: firm-level P&L, desk or strategy level P&L and qualitative impact (including infrastructure improvements, data quality, execution, or risk management that might not directly show up in P&L). 

The opacity of discretionary bonuses is often far more intentional than not, giving management flexibility to calibrate payouts across environments, following a ‘’benefit for all’’ attitude regardless of performance. For quants, this often translates into operating with incomplete information about how their compensation is actually determined and how contribution is effectively attributed. 

On the contrary, some firms opt for a team-based and/or individual attribution model to emphasise individual credit for a model or signal and ultimately encourage collaboration, but it comes at a trade-off. On one hand, individualised structures can incentivise innovation and ownership but risk creating silos, while on the other hand, team pools strengthen knowledge sharing and code quality but can dilute recognition for standout contributions. These structural choices within firms reveal not only a firm’s internal culture but the workforce behaviours it truly values. 

Beyond the annual cycle, firms use longer-dated levers to retain researchers without exposing them to mark-to-market volatility, including deferred bonuses that tend to vest over several years, co-investment programmes that allow researchers to allocate personal capital into firm funds and phantom equity or profit-sharing units, especially at larger multi-managers or asset management-style platforms. While less common in quant-centric firms, long-term incentives are becoming more prevalent as firms compete with AI labs and compute-heavy research groups for the same talent pool.

Beyond money, firms use levers that significantly affect perceived ‘’compensation", including access to compute and datasets, autonomy in research direction, visibility with capital allocators, pathways to run a book or influence strategy design, and the ability to focus on long-term research rather than firefighting. For many quants, often these non-monetary elements drive satisfaction and retention more than incremental cash. 

The key point is simple: once base pay is generous everywhere, incentives live in attribution systems and research conditions. Compensation becomes a behavioural tool, not just a reward.

Geographical remuneration biases?

Despite the sophistication of quant finance, the global market for quant talent is far from frictionless. Compensation varies meaningfully across geographies, even when the work, skill level, and impact are equivalent. The result is a quiet but persistent geographical arbitrage: the same human capital is systematically valued differently depending on where it sits.

1. New York: The Persistent Premium

New York remains the undisputed centre of gravity for quant compensation, a position reinforced by consistently higher base salaries, deeper bonus pools, and a concentration of capital that few other regions can match. This premium is driven not only by revenue per seat but by the intensity of local competition: New York firms must contend directly with Big Tech, cutting-edge AI labs, and elite academic institutions for the same narrow pool of mathematically exceptional talent. As a result, quants in the U.S. typically earn 20–40% more in total compensation than their counterparts in London or Singapore, even when performing identical work. This disparity has become a structural feature of the industry, one that shapes both where firms build teams and where researchers choose to build careers.

2. London: High But Still Discounted

London remains Europe’s quant hub, but the pay gradient persists. Despite expensive cost of living and deep financial infrastructure, London compensation bands often trail New York by a noticeable margin. Some of this is cultural (Europe’s preference for flatter pay distributions), and some regulatory (bonus caps in historically bank-aligned groups, even though hedge funds are exempt). For equivalent roles in systematic shops, comp often comes in 10–20% below U.S. benchmarks, even when the underlying P&L exposure is similar.

3. Asia: A High-Talent Pool at a Lower Price Point

Singapore and Hong Kong host world-class quants, but pay levels often lag both New York and London. Despite being global financial hubs, Asian offices frequently face a discounted compensation structure. Firms rationalise this through lower local costs, different market liquidity profiles, or strategic positioning of research teams. But in practice, firms also benefit from a market where top candidates, especially those trained locally, may have fewer competing employers offering U.S.-style packages.

These geographical pay gaps persist for reasons that are more structural than strategic. Firms often justify compensation differences through cost-of-living or tax narratives, though these are frequently overstated when comparing cities like London, Singapore, and New York, all of which are among the world’s most expensive. A deeper explanation lies in the differing competitive landscapes: New York employers must compete directly with FAANG, top AI labs, and elite research institutions for quant talent, while Europe and Asia still offer fewer alternative employers willing to match U.S. compensation levels. Regulatory and cultural constraints around pay dispersion further compress salaries in certain markets, particularly in Europe where compensation norms and historic banking regulations have shaped expectations. Add to this a persistent information asymmetry, where local candidates often lack visibility into global benchmarks, and the result is a predictable but rarely acknowledged arbitrage. The irony is difficult to ignore: an industry built on exploiting inefficiencies tolerates a glaring one within its own labour market.

These discrepancies, however rationalised, shape incentives and career behaviour in subtle but influential ways. Senior quants often relocate to the U.S. to maximise compensation, creating a self-reinforcing talent concentration in American hubs. Firms, for their part, tend to cluster their highest-value research roles in regions where they believe the talent–capital equation is most favourable, further widening the gap. Global teams can experience uneven perceptions of recognition and impact, as researchers in discounted geographies may feel structurally undervalued despite producing equivalent work. Ultimately, incentives in quant finance are not merely a function of role or performance, they are deeply shaped by geography. 

Conclusion

Taken together, the pay market for systematic quants appears efficient on the surface. In practice, incentives are driven by less visible mechanics: attribution systems, long-dated retention tools, and persistent geographical arbitrage. For both firms and researchers, understanding these underlying structures matters far more than memorising headline numbers.