Quant Research Engineer

Company

Optima is building AI-native wealth for the new India. Our culture and the longer story: https://optima.ai/talent

The Idea

Every systematic fund runs one book against one objective. We run a different book for every client — each with their own concentration, their own constraints, their own definition of 'safer.' Low frequency, multi-asset, primarily Indian equity, and every position explainable to the person who owns it.

That makes this a harder research problem than a normal fund, not an easier one. You're not optimizing a portfolio — you're optimizing a space of personalized portfolios, and proving each one to its owner. 'Think hedge fund, but personal' is the quant problem, not the marketing.

The edge isn't latency. It's how fast you get from a hypothesis to an experiment clean enough to kill it or trust it — and how fast that turns into a better book. We need someone who owns that.

The role

• Go from hypothesis to evidence, fast. You see what the book should try, design the experiment that settles it, and know within days whether it's real or noise. Research velocity is the job. The eval and backtesting machinery that keeps you honest is yours to build and keep good.
• Own personalization as a research problem. Per-client construction, concentration, and constraints at low frequency — and the explanation of why each book holds what it holds — are yours. This is the part no other systematic fund has solved, and it's the reason the role exists.
• Ship into live mandates. Research that stays in a notebook doesn't count. You pair with someone who owns the engine the research runs on; you own the thesis, the evidence, and the call to put it into production. You build what you need to move.
• Absorb the regulatory frame. We're a SEBI PMS. Compliance and benchmarking are constraints you fold into better systems, not friction you push downstream.

Who this is for

• You've done systematic research that reached production and touched real money — as a quant researcher, a systematic PM, or quietly both.
• 4+ years where the edge was the quality of your research and the honesty of your evaluation.
• You think in signals, drawdowns, and evals — and you have a real story of an anomaly nobody flagged, deciding what it meant, and acting on it.
• Multi-asset, low-frequency instinct: you reason about regime, concentration, and risk at the portfolio level, not the tick level.
• Strong quant+engineering signal (IIT CSE / MnC, PhD, or equivalent) helps but does not substitute for the above.

What this isn't

• Not HFT or microstructure.
• Not backtest-and-toss. If your work has ended at a notebook for someone else to productionize, this isn't it.
• Not a discretionary PM seat. You want a system that decides well, not a book you trade by hand.
• Not a pure infra role.

Highlights

• Mumbai, on-site
• Top-of-market compensation
• ESOPs
• Health insurance

To apply

Don't send a resume first. Send us something you researched and shipped that you're proud of, and the story of why that and not something else, including what the evidence told you: [HIDDEN TEXT]

Skills Required
backtesting