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Equity Quantitative Researcher

at Point72

Back to all Python jobs
Point72 logo
Hedge Funds

Equity Quantitative Researcher

at Point72

ExperiencedNo visa sponsorshippython

Posted 2 hours ago

0 clicks

Compensation
$150,000 – $200,000 USD

Currency: $ (USD)

City
New York
Country
United States

A Cubist portfolio management team is seeking a research analyst to perform rigorous and innovative research to discover systematic anomalies in the equity market. The role involves end-to-end development including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation.

Role/Responsibilities

  • Perform rigorous and innovative research to discover systematic anomalies in equity market
  • End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization and production implementation
  • Identify and evaluate new datasets for stock return predictions
  • Maintain and improve the portfolio trading in production environment

Requirements

  • MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics
  • 1+ years of work experience in systematic alpha research in equities
  • Experience developing short term alpha signals (intraday or a few days) is a plus
  • Demonstrated proficiency in R or Python
  • Strong command of foundations of applied statistics, linear algebra, and time series models
  • Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources
  • Strong knowledge of financial markets
  • Highly motivated, willing to take ownership of his/her work
  • Collaborative mindset with strong independent research ability

The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.


Equity Quantitative Researcher

at Point72

Back to all Python jobs
Point72 logo
Hedge Funds

Equity Quantitative Researcher

at Point72

ExperiencedNo visa sponsorshippython

Posted 2 hours ago

0 clicks

Compensation
$150,000 – $200,000 USD

Currency: $ (USD)

City
New York
Country
United States

A Cubist portfolio management team is seeking a research analyst to perform rigorous and innovative research to discover systematic anomalies in the equity market. The role involves end-to-end development including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation.

Role/Responsibilities

  • Perform rigorous and innovative research to discover systematic anomalies in equity market
  • End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization and production implementation
  • Identify and evaluate new datasets for stock return predictions
  • Maintain and improve the portfolio trading in production environment

Requirements

  • MS or PhD in physics, engineering, statistics, applied math, quantitative finance or other quantitative fields with a strong foundation in statistics
  • 1+ years of work experience in systematic alpha research in equities
  • Experience developing short term alpha signals (intraday or a few days) is a plus
  • Demonstrated proficiency in R or Python
  • Strong command of foundations of applied statistics, linear algebra, and time series models
  • Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources
  • Strong knowledge of financial markets
  • Highly motivated, willing to take ownership of his/her work
  • Collaborative mindset with strong independent research ability

The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.