Mid-Level Quantitative Researcher
Austin Community College
Mid-Level Quantitative Researcher
Location: Stamford, CT
Team: Relative Value Volatility Strategies
Reports to: Deputy CIO
Overview
We are seeking a mid-level quantitative researcher to join our investment team focused on relative-value volatility trading strategies across equities, indices, fx, rates, and credit. The role will combine quantitative modeling, data engineering, and applied research, supporting semi-systematic trading initiatives.
The ideal candidate will have strong Python programming skills, experience with cloud-based data platforms (Snowflake preferred), and a background in volatility products, derivatives, or other complex instruments.
Key Responsibilities
- Research and implement relative-value volatility strategies, including spread, curve, and cross-asset vol relationships.
- Build and enhance quantitative models for pricing, and signal generation.
- Analyze historical and real-time market data to identify dislocations and arbitrage opportunities.
- Work with large structured and unstructured datasets in Snowflake, ensuring data integrity and accessibility.
- Develop Python-based research and production tools for backtesting, trade simulation, and performance attribution.
- Collaborate across the team to translate research into executable strategies.
- Present research findings in a clear, concise manner to senior stakeholders.
Qualifications
- 3–6 years of experience as a quantitative researcher, strategist, or data scientist in a hedge fund, bank, or trading firm.
- Solid understanding of volatility products and derivatives (e.g., options, variance swaps, VIX futures, volatility indices).
- Proficiency in Python for research, modeling, and data pipelines.
- Hands‑on experience with Snowflake or similar cloud-based data warehouses.
- Strong quantitative background (statistics, econometrics, applied math, or financial engineering).
- Familiarity with time-series modeling, machine learning, or risk factor analysis.
- Ability to work in a fast-paced, collaborative, and entrepreneurial environment.
Preferred Skills
- Experience with systematic volatility strategies (relative value, dispersion, correlation, skew).
- Background in SQL, data engineering, and APIs for market data ingestion.
- Exposure to portfolio construction, PnL attribution, and risk modeling.
- Advanced degree (MS/PhD) in a quantitative field is a plus.
Vacancy posted 15 hours ago
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