Global Equities Quant Researcher - Systematic Trading

Old Mission; New York (NY); Sur place; USD 200 000 - 350 000; Plein temps

Avantages offerts par ce poste

Competitive salary with discretionary年

Fully paid private medical, dental, or

Free on-site lunch daily

Tuition Reimbursement Program

Résumé du poste

Old Mission is seeking a Quantitative Researcher for its Global Equities team in New York City. You will design, research, and deploy systematic trading strategies across worldwide equity markets with end-to-end ownership from alpha generation to signal research.

Responsibilities include backtesting, risk-aware portfolio construction, and performance evaluation, in collaboration with engineers and traders. A strong Python background and experience with large financial datasets are required.

Qualifications

• Quantitative researcher with strong analytical skills.
• Ability to manage multiple work streams and communicate clearly.
• Experience handling large datasets and building research pipelines.
• Attention to detail and high ethical standards.

Responsabilités

• Research, develop, and implement quantitative trading strategies across global equity markets.
• Identify and test alpha signals using large datasets.
• Perform statistical analysis, feature engineering, and model validation.
• Design portfolio construction and optimization with risk constraints and costs.
• Backtest, validate, and attribute performance of strategies.
• Collaborate with researchers, traders, and engineers to productionize models.
• Monitor live strategies and iterate to improve risk-adjusted returns.
• Evaluate new data sources and regime changes.

Formation

Bachelor's or higher degree in Mathematics, Physics, Statistics, Computer Science, or Operations Research

Outils

Python

Description du poste

Old Mission is seeking a Quantitative Researcher for its Global Equities team in New York City. You will design, research, and deploy systematic trading strategies across worldwide equity markets with end-to-end ownership from alpha generation to signal research.

Responsibilities include backtesting, risk-aware portfolio construction, and performance evaluation, in collaboration with engineers and traders. A strong Python background and experience with large financial datasets are required.