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Point72
Verified live 1d ago

Equity Quantitative Researcher

Brief overview

New York, New York, United StatesIn-person
MastersOr in progress
1+ yrsMinimum
135 H-1B approvalsDept. of Labor
43 green cardsCertified filings
RPythonapplied statisticslinear algebratime series modelsdata processingbacktestingalpha researchfinancial markets

About the company

Point72 invests in multiple asset classes and strategies worldwide.

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
135H-1B approved
99%approval rate
30new H-1B hires
43PERM certified
$222,500median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202361
202472
20252
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202324
202417
202517
202625
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
202310
202412
202518
20263
Top sponsored roles
Quantitative Software DeveloperQuantitative Strategist, Macro TechnologyData AnalystIT Operations Engineer, Application SupportQuantitative Strategist, Treasury Quant Strategy
Sponsored employees from
ChinaIndiaUnited KingdomMalaysiaGermany

Job description

ROLE/RESPONSIBILITES

  • 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

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