Quant Researcher — Full-time

Anthelion Capital; New York (NY); On-site; USD 120,000 - 240,000; Full time

Job summary

Anthelion Capital is a research‑driven investment firm building a proprietary data science platform to run the full investment lifecycle.

You will build predictive signals, validate them rigorously, and collaborate with portfolio managers to allocate capital based on real results. You will own datasets and signals from idea to live production, extend data pipelines, and shape the research platform while guarding against overfitting and look‑ahead bias.

Qualifications

• PhD or master's in a quantitative field (or exceptional undergrad).
• Depth in statistics and/or machine learning.
• Comfortable with Python and large, messy datasets.
• Rigorous about overfitting and look‑ahead bias; strong research discipline.

Responsibilities

• Build predictive signals that drive real trading decisions.
• Generate original signals, validate them rigorously, and work with portfolio managers to allocate against real capital.
• Own assigned datasets and signals—from idea to live signal on the platform.
• Source, curate, and shape datasets into validated factors for the shared data pipelines.
• Turn research into production by moving signals from notebook to running, monitored pipelines.
• Contribute to shaping the research platform, factor library, and prod conventions.

Skills

Statistics

Machine Learning

Python

Data Engineering

Research

Education

PhD or Masters in quantitative field (or exceptional undergrad)

Job description

About Anthelion

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.