About the Role:
We are seeking a talented and intellectually curious Quantitative Researcher to join our Systematic Equities team. In this role, you’ll design, test, and implement statistically driven equity strategies using large-scale datasets and advanced research tools. You will contribute directly to alpha generation and portfolio construction for long/short and market-neutral mandates.
This is an ideal opportunity for someone with strong quantitative and programming skills who thrives in a fast-paced, research-driven environment and is passionate about applying scientific methods to financial markets.
Key Responsibilities:
- Research and develop systematic investment strategies in global equity markets using statistical and machine learning techniques
- Analyze large volumes of structured and unstructured data to extract predictive signals (alpha factors)
- Build, backtest, and validate factor models, portfolio optimizations, and risk management frameworks
- Collaborate with data engineers and technologists to streamline the research infrastructure and datasets
- Monitor and improve live strategies by conducting performance attribution and identifying degradation or new opportunities
- Present research findings and investment theses to portfolio managers and leadership
Required Qualifications:
- Master’s or PhD in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Financial Engineering, or similar
- 2–7+ years of hands-on experience in systematic equities or quantitative research at a hedge fund, asset manager, or proprietary trading firm
- Deep expertise in statistical modeling, time series analysis, and signal processing
- Strong coding skills in Python (preferred), R, MATLAB, or C++
- Solid understanding of portfolio theory, risk modeling, and execution costs
- Experience working with financial datasets such as Bloomberg, FactSet, Refinitiv, or alternative data sources
Preferred Qualifications:
- Familiarity with machine learning frameworks (e.g., XGBoost, LightGBM, sklearn, PyTorch) applied to financial data
- Experience developing medium- to high-frequency strategies or factor models (value, momentum, quality, etc.)
- Knowledge of optimization libraries and transaction cost modeling
- Understanding of market microstructure, exchange behavior, or global regulatory dynamics
What We Offer:
- A research-first, collaborative environment with direct impact on live portfolios
- Exposure to global equity markets and state-of-the-art research infrastructure
- Competitive compensation with performance-linked incentives and long-term career growth
- Flexible work setup, top-tier tools, and access to proprietary data sources
- Mentorship from senior quant researchers and technologists
How to Apply:
📩 Please send your resume, a brief research summary or sample project, and GitHub (if available) to: careers@yourcompany.com
Subject: Application – Quantitative Researcher (Systematic Equities) – [Your Name]
🗓 Applications reviewed on a rolling basis with confidentiality assured