Experienced Quantitative Portfolio Manager or Strategist NY

About the Opportunity

Kershner Trading Group and SMB Capital, a joint venture of leading proprietary trading and technology firms with offices in New York, Austin, and Chicago, are seeking Experienced Quantitative Portfolio Managers / Strategists for the U.S. equity market and Crypto currency.

Responsibilities

• Develop new trading strategies
• Utilize cutting edge data platform
• Work with high performance elastic research and trading infrastructure
• Receive investment capital and trader coaching/support
• Access rich datasets for analysis

About You

Ideal candidates will have an MS or PhD in an Engineering or Pure Science discipline with expertise in alpha research, portfolio construction, risk management and trade execution. Relevant quantitative skill sets include Artificial Intelligence, Machine Learning, Natural Language Processing, Portfolio Optimization, Linear Programming, Time Series Prediction, Factor Analysis and/or Fundamental Equity Valuation. Candidates should have a proficiency in one of the following programming languages: Python (preferred) and/or C++, C#, Java or R.

Eligibility

Candidates should have a recent track record or demonstrate a direct contribution to profitable systematic trading strategies or process in U.S. Equities and cryptos. Intraday strategies and medium to high frequency are preferred. Experience with futures, FX and international equity trading is also a plus. Candidates should have the ability to deploy and manage trading strategies from inception.

Benefits

• Opportunities available in the New York office
• Some options available for remote teams and team members

About Company

Kershner Trading Group / SMB Capital is a collaborative research environment seeking individuals with a strong entrepreneurial spirit, exceptional work ethic, and strong analytical skills to develop new trading strategies. The firm provides a state-of-the-art research environment ideal for machine learning, integrated simulation and production environments with co-located execution engines and advanced risk management and monitoring tools.