Senior Quantitative Portfolio Strategist - U.S. Equities

Kershner Trading Group; New York (NY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

A trading firm in New York seeks an Experienced Quantitative Portfolio Manager or Strategist to develop new trading strategies for U.S. equities and cryptocurrencies. The ideal candidate holds an MS or PhD in an Engineering or Pure Science discipline and has expertise in alpha research and quantitative methods. This role offers full-time employment in a collaborative research environment with options for remote work.

Qualifications

• Expertise in alpha research, portfolio construction, and risk management.
• Proven track record of contributions to profitable systematic trading strategies.
• Experience with trading U.S. equities and cryptocurrencies.

Responsibilities

• Develop new trading strategies for U.S. equity market and cryptocurrency.
• Utilize the firm’s data platform for research and testing.
• Contribute to quantitative research and backtesting.

Skills

Artificial Intelligence

Machine Learning

Natural Language Processing

Portfolio Optimization

Linear Programming

Time Series Prediction

Factor Analysis

Education

MS or PhD in an Engineering or Pure Science discipline

Tools

Python

C++

C#

Java

R

Job description

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.

Kershner Trading Group / SMB Capital is a collaborative research environment and is

seeking individuals with a strong entrepreneurial spirit, exceptional work ethic, and

strong analytical skills to develop new trading strategies. The firm provides a cutting

edge data platform, high performance elastic research and trading infrastructure,

investment capital and trader coaching/support. We provide access to rich datasets

(e.g., tick data, fundamental datasets, sentiment and other alternative datasets), 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.

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. Candidate should have

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.

Opportunities are available in the New York office with some options available for

remote teams and team members.