Quant Developer — Full-time
$120,000–$240,000 year
On-siteNew York City, New York, United States
Job Summary
Own the quant engineering platform end to end by building the shared data layer, backtesting engine, portfolio-construction libraries, and model deployment pipeline. Manage market and reference data ingestion, feature stores, and Dagster asset graphs to ensure point-in-time correctness. Support live models with monitoring and observability while collaborating directly with researchers and portfolio managers on strategy diagnostics and scenario analysis. Requires onsite presence in Midtown, New York City at least three days per week, with a base salary range of $120,000 to $240,000 and eligibility for discretionary bonuses. Candidates must be authorized to work in the United States without visa sponsorship.
Required Qualifications
- Strong software engineering: Python
- Strong software engineering: at least one systems language
- Strong software engineering: good design instincts
- Strong software engineering: the ability to build tooling other people depend on
- Solid grounding in quantitative finance
- Solid grounding in quantitative finance: understanding what a Sharpe ratio actually means
- Solid grounding in quantitative finance: understanding what a risk factor actually means
- Solid grounding in quantitative finance: understanding what a backtest actually means
- Solid grounding in quantitative finance: understanding what a portfolio optimizer actually means
- Solid grounding in quantitative finance: understanding why these things are built the way they are
- Data engineering chops: pipelines
- Data engineering chops: correctness under time (as-of-date / point-in-time)
- Data engineering chops: reliability
- A platform mindset: repeatable, guard-railed, self-service tooling over one-off scripts
- Must be authorized to work in the United States without employer visa sponsorship
- Location : Onsite in Midtown, New York City at least 3 days per week
Desired Qualifications
- Nice to have: Dagster/Prefect
- Nice to have: Azure
- Nice to have: model-registry or feature-store experience
- Nice to have: prior work at a quant/trading firm
- Nice to have: a serious data platform
- Nice to have: hands-on risk-modeling or portfolio-construction experience
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