Quantitative Researcher (Systematic Equities)

Quantitative Researcher (Systematic Equities)

Location: NYC or Greenwich, CT

Team: Systematic Equities PM Team

About the Role:

We are seeking a highly motivated and technically skilled Mid-Frequency Equities Quantitative Researcher to join our growing team. This individual will focus on alpha research in US equity markets, with additional exposure to global developed markets, including EU. The ideal candidate will possess a strong background in both technical and fundamental alpha research with practical experience leveraging alternative datasets and cutting-edge machine learning techniques. The ideal candidate will possess a keen ability to source, evaluate, and extract value from complex datasets.

Key Responsibilities:

• Conduct mid-frequency alpha research with a focus on US equities, and support global equities research in developed EU markets.
• Design, test, and implement technical alphas using market microstructure signals, including price/volume, and other market data.
• Develop and evaluate fundamental alpha signals by leveraging alternative data sources (e.g., web data, satellite imagery, transactional data, analyst data, events data, etc.).
• Perform robust data preprocessing, feature engineering, and transformation pipelines to extract predictive signals.
• Apply and adapt machine learning models to improve the efficacy and robustness of alpha signals.
• Perform rigorous backtesting and statistical validation of alphas.
• Lead rigorous data quality assessments to ensure the integrity, consistency, and completeness of new and existing datasets before incorporating them into the research process.
• Work collaboratively to implement and monitor alpha strategies in production.
• Maintain high standards of research documentation and reproducibility.

Qualifications:

• 3+ years of experience in quantitative research, preferably in equities-focused alpha signal development.
• Demonstrated experience developing both technical alphas (based on market microstructure data) and fundamental alphas (leveraging alternative data).
• Strong programming skills in Python; experience with research platforms and data analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Solid understanding of statistical techniques, data cleaning, and feature engineering.
• Applied experience with machine learning techniques in alpha research.
• Strong understanding of backtesting methodologies and model validation techniques.
• Familiarity with global equity markets, particularly developed EU markets, is a plus.
• Masters or Ph.D. in a quantitative discipline such as Computer Science, Mathematics, Physics, Engineering, or Finance, (or equivalent).

Preferred Attributes:

• Exceptional attention to detail, particularly in the context of handling large, noisy, or novel datasets.
• Demonstrated ability to work independently in a fast-paced, data-driven environment.
• Strong communication skills, with the ability to present research findings clearly and concisely.
• Detail-oriented mindset with a strong commitment to code quality and research reproducibility.