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Quantitative Researcher - Semi-Systematic Trading

Location

New York, NY

JobType

full-time

About the job

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About the role

Empowering Global Markets

Summit Securities Group provides liquidity and transparency to electronic financial markets across the globe. Our skilled team of cross-functional experts engage in quantitative and algorithmic trading to generate exceptional results in highly competitive and rapidly changing global financial markets.

The Role

We are seeking a Senior Quantitative Researcher to join our established semi-systematic trading team. As a senior member, you will play a pivotal role in shaping the team’s continued success, bringing a seasoned perspective for what constitutes robust, alpha-generating research. You will collaborate with traders and fellow researchers to elevate our strategies and frameworks, directly impacting the desk’s P&L.

Responsibilities

  • Portfolio & Risk Optimization: Drive portfolio construction by applying advanced optimization techniques to holistically manage risk, alpha, and transaction costs.
  • Alpha & Strategy Modeling: Lead the end-to-end research, modeling, and validation of new alpha signals, setting the standard for a high-quality, tradable strategy.
  • Rigorous Validation: Evolve the team’s backtesting frameworks to rigorously stress-test strategies, identify hidden biases, and create deep performance analytics to explain P&L realization.
  • Intellectual Leadership: Provide intellectual leadership by shaping the research agenda, mentoring team members, and driving a culture of scientific rigor and collaboration.

You Bring

  • Education: BA/BS or an advanced degree in a highly quantitative field such as Statistics, Mathematics, Physics, Computer Science, or Engineering.
  • Experience: 5+ years of direct experience in a quantitative research role. You have a demonstrable history of navigating the full research lifecycle and have developed a strong, opinionated view on what good research looks like.
  • Skills:
    • Expert-level programming skills in Python and its scientific computing stack (Pandas, NumPy, SciPy, scikit-learn).
    • Mathematical Optimization: Deep, practical experience with linear/quadratic programming, convex optimization, and other techniques as they apply to portfolio construction and financial modeling.
    • Applied Statistics & Machine Learning: A master practitioner's knowledge of statistics, econometrics, and ML, knowing which tool to apply to which problem.
  • Professional Acumen: Deep, applied mastery of the following:
    • Factor Modeling: A refined "taste" for what makes a good alpha factor, born from years of experience.
    • Portfolio Construction: An intuitive and quantitative grasp of building and managing multi-factor portfolios.
    • Robust Validation: An ingrained skepticism and a toolkit for validating research that goes far beyond standard backtesting metrics.
  • Behavioral: Strong intellectual conviction paired with low ego. A relentless drive to find the truth in data and the ability to defend research with clarity and rigor. An ownership mentality and the maturity to navigate the inherent ambiguity of financial markets.
We Offer

At our firm, our people come first. We are committed to building a culture of collaboration, where we support each other through challenges and celebrate our collective successes. We believe that the strength of a modern workplace lies in its diverse workforce—diverse in ideas, cultures, and experiences. We actively foster this environment and take pride in being an equal opportunity employer. In compliance with New York City’s Pay Transparency Law, the anticipated base salary for this role ranges from $150,000 - $250,000 annually, based on experience and qualifications. Please note, this range excludes other components of total compensation, such as bonuses.

We offer competitive compensation packages, company equity, 401k matching, gender-neutral parental leave, and comprehensive medical, dental, and vision insurance. While we value flexibility, we believe that in-person collaboration is key to solving complex challenges, which is why we require employees to be in the office 4 days a week. In-office perks include lunch stipends, fully stocked kitchens, happy hours, and a great location with amazing colleagues.

Our top priority is our people. We invest in a culture that promotes togetherness, helping each other through challenges and celebrating each other's successes. We believe that modern workplaces succeed by having diverse high-performance workforces — in ideas, in cultures, and in experiences. We put in the effort to make such a workplace a daily reality and are proud to be an equal opportunity employer.

PI273758939

Skills

Python
compliance
cross-functional
econometrics
end-to-end
NumPy
Pandas
statistics