Software Engineer

Senior Quant Developer - Analytics New York City | Hybrid preferred · Remote considered for exceptional candidates

You've probably scrolled past a dozen of these this month.

Most blur together. "Cutting-edge." "Fast-paced." "Mission-driven." Vague promises about impact, vaguer promises about comp. So let's skip that part.

Here is the honest version.

The seat, in one paragraph
You would build the analytics platform that risk managers and portfolio managers actually use to make decisions across asset classes, across time horizons, across the what-if scenarios that have to compute quickly and correctly for a top trading firm. Roughly 75% software engineering, 25% quantitative modeling. The math is not decorative. The people you serve will tell you within minutes if it is wrong.

What you would actually do
Partner directly with quants and risk managers to design pricing, risk, and scenario analytics across derivatives, rates, and multi-asset portfolios
Architect platforms that compute analytic measures over arbitrary time horizons not just snapshots, not just close-of-day
Take complex quantitative requirements and turn them into systems that are testable, observable, and easy to change six months from now
Own production. On-call is shared across US and UK time zones, so it is not punishing.

The Tech Stack
Roughly half Elixir, half Python. C++ analytics libraries underneath.
You probably have not written Elixir before. Almost no one has. That is expected. It was chosen deliberately, concurrency and distributed systems, and engineers who were curious about it tend to love it once they are in. If "I would have to learn a new language" is a dealbreaker, this is a useful early signal for both of us.

You will use your preferred language throughout the entire interview process. Python person? Do the take-home in Python. Java person? Do it in Java. We are hiring engineers, not language collectors.

We are looking for someone who...
Has roughly 6+ years building real software in the financial industry, asset manager, prop firm, hedge fund, fintech sitting on top of a risk platform, or the right slice of an investment bank
Has touched pricing, risk, or trading analytics in a meaningful way. This is the non-negotiable.
Has enough quantitative depth to read a paper, push back on a quant's spec, and actually shape the model not just translate it into code
Designs systems before writing them, and can talk about that design clearly
Communicates like the adult in the room. The role lives in front of internal clients.

What we are honestly NOT looking for
So neither of us wastes time:
Pure backend / SaaS engineers with no financial services exposure. We have run this experiment. It does not convert.
Big-bank engineers who have owned 4% of one risk system for seven years. Siloed CVs look strong on paper and then come apart at the architecture deep-dive. If your role has been broader than your title suggests, tell us, we will dig.
Engineers who want the math kept behind a wall. Here, the math is the job.

If any of the above describes you and you are reading this thinking "actually, no let me explain why I am the exception," that is exactly the conversation we want to have. Tell us why.
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