
Posted 2 months ago
Quant Researcher — Full-time
AI Summary
A research-first Quant Researcher who builds predictive signals, validates them rigorously, and runs them through production pipelines, owning datasets and factors from idea to live signal.
About this role
Anthelion Capital is an investment and data science platform. We augment our fundamental investment core with data science to make investments across the capital structure. We are building a proprietary platform that runs the full investment lifecycle, from underwriting to portfolio management.
What you'll do. Build predictive signals that drive real trading decisions. You'll generate original signals, validate them rigorously, and work with portfolio managers to get them allocated against real capital — with the platform taking you from notebook to monitored pipeline. This is a research-first seat.
What you'll own:
· Your assigned datasets and signals — from idea, to validated factor, to a live signal on the platform.
· The research quality, robustness, and out-of-sample validity of your signals — you're accountable for whether they hold up, not just whether they backtest well.
· Sourcing and curating the datasets your signals need — including novel or alternative data — and shaping them into validated factors. The data pipeline is a shared build — you'll extend and harden it alongside the platform team, not just consume it.
· Turning your own research into production — taking a signal from notebook to a running, monitored pipeline via the research-to-production path.
· A voice in shaping the research platform — the factor library, templates, and research-to-prod conventions — as one of its primary users.
We're looking for:
· PhD or master's (or an exceptional undergrad) in a quantitative field — statistics, math, physics, CS, or similar.
· New grad through experienced hires.
· Depth in statistics and/or machine learning, and a demonstrated research track record.
· Rigor about overfitting, multiple-hypothesis pitfalls, look-ahead bias, and point-in-time discipline — the instinct to distrust a clean result.
· Comfortable in Python and working with large, messy datasets.
· Solid data-engineering comfort — you'll source, curate, and help build the shared data pipelines your research runs on, not just query what someone else prepared.
· Nice to have: time-series / financial modeling, prior systematic-investing or quant-research experience, publications or competition results.
Additional Details:
Compensation: Base salary of $120,000 to $240,000 depending on experience. Eligible for performance based discretionary bonus.
Location : Onsite in Midtown, New York City at least 3 days per week.
Other : Must be authorized to work in the United States without employer visa sponsorship.
Skills
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