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Quant Developer

Dark Alpha Capital LLC
Email

Quant Developer

Location: Remote
Compensation: 5% of Net Carry for deployed strategies
Reports To: CIO / Managing Partner

About Dark Alpha Capital

Dark Alpha Capital is an emerging investment firm currently operating as a proprietary trading group, deploying the Managing Partner’s capital across systematic, quantitative, and event-driven strategies. Our near-term goal is to build a multi-year, independently audited track record by developing disciplined, repeatable, and scalable trading processes.

Once our methods are proven and performance is validated, we plan to raise outside capital and transition into a fully structured hedge fund. Early hires will help architect the research engine, execution systems, and data infrastructure that form the foundation of the future fund.

Role Overview

The Quant Developer will design, test, and implement systematic trading strategies that directly impact Dark Alpha Capital’s proprietary trading program. You will work closely with the CIO and Portfolio Managers to convert research insights into robust, production-ready models that drive live trading and long-term track-record creation.

Key Responsibilities

  • Research, design, and implement systematic and algorithmic trading strategies.
  • Build, clean, and maintain large datasets for model development and monitoring.
  • Conduct backtesting, walk-forward analysis, Monte Carlo simulations, and performance stress testing.
  • Apply econometric and statistical techniques (linear regression, probability models, time-series analysis).
  • Study market microstructure to optimize execution and reduce slippage.
  • Build automated pipelines for ingestion, cleaning, structuring, and storage of data.
  • Collaborate with PMs and CIO to deploy validated strategies into production.
  • Produce clear research documentation and performance analytics.

Qualifications

  • Bachelor’s in Computer Science, Mathematics, Physics, Engineering, or quantitative field.
  • Strong programming skills in Python and SQL.
  • Experience working with large datasets and data pipelines.
  • Knowledge of econometrics, statistics, probability theory, and regression modeling.
  • Understanding of financial markets and market microstructure.
  • 2+ years of quant research, modeling, or algorithmic trading experience.
  • Ability to build reproducible, validated research output.