Senior Quantitative Portfolio Strategist
2 weeks ago
Kershner Trading Group, a prominent proprietary trading and technology firm, is in search of Senior Quantitative Portfolio Managers / Strategists specializing in the U.S. equity market and cryptocurrency.
This role is situated within a dynamic research environment that values collaboration and innovation. We are looking for candidates who possess a strong entrepreneurial mindset, a remarkable work ethic, and exceptional analytical capabilities to formulate and enhance trading strategies.
The firm offers a state-of-the-art data platform, high-performance research and trading infrastructure, along with investment capital and comprehensive trader support.
We provide access to extensive datasets, including tick data, fundamental datasets, sentiment analysis, and other alternative data sources. Our research environment is tailored for advanced machine learning applications, featuring integrated simulation and production settings with co-located execution engines and sophisticated risk management tools.
Ideal candidates will hold an MS or PhD in an Engineering or Pure Science discipline, with a focus on alpha research, portfolio construction, risk management, and trade execution.
Key quantitative skills should encompass:
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Portfolio Optimization
- Linear Programming
- Time Series Prediction
- Factor Analysis
- Fundamental Equity Valuation
Proficiency in programming languages such as Python (preferred), C++, C#, Java, or R is essential. Candidates should demonstrate a recent track record or a significant contribution to profitable systematic trading strategies or processes in U.S. equities and cryptocurrencies. Experience with intraday strategies and medium to high-frequency trading is preferred, along with familiarity in futures, FX, and international equity trading.
Successful candidates will have the capability to deploy and manage trading strategies from inception.
Opportunities are available with flexible options for remote collaboration.
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