Role: Quantitative Researcher - Trade Cost Analyst
Venture Search is partnered with a leading global hedge fund. The firm has over 20 years of experience and manages under $ 40 billion in assets spanning multi-asset classes.
The firm has global coverage but this would be for an opening in their New York location.
This would be an exciting opportunity to join the firm's trading research team which employs quantitative methods to trade across Futures, FX, Rates, and Equities.
The role:
- Assess and optimize the performance of our trading strategies, enhancing and refining trading algorithms, and developing methods for comparing different execution strategies. Collaborate with brokers and Portfolio Managers to improve execution.
- Design, develop, and continuously refine the transaction cost analysis (TCA) framework.
- Build and maintain frameworks for execution performance measurement and attribution, including dashboards and reporting tools.
- Utilize pricing and reference data, such as tick and order book level data, to perform in-depth execution performance analysis.
- Leverage advanced statistical techniques, market impact models, and limit order models to work with columnar databases, conducting detailed time series analysis.
- Collaborate with systematic leadership and trading teams to translate business needs into scalable, standardized solutions.
- Perform statistical analysis on large datasets to uncover insights and inform trading decisions.
- Establish and uphold engineering best practices, ensuring high standards throughout the entire software development lifecycle (SDLC).
Experience:
- Over +5 of experience
- MS or PhD in fields such as Statistics, Computer Science, Financial Engineering
- Experience with databases such as KDB
- Strong understanding of market structure spanning various asset classes
- Extensive experience in Python libraries such as Pandas, matplotlib, and Sklearn, etc.
- Hands-on experience of working with tick data. Proficient in advanced statistical techniques, market impact models, time series analysis, and coding with columnar/time series databases such as SQL.
- Excellent quantitative reasoning and a strong interest in combining research and software engineering.