Tech- Macro Quantitative Strategist

 

Company Overview
Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy.

Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically with a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.

At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.

Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.

Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.

Team Overview
The Quantitative Development and Strategy team is responsible for research and analytics technology at SFM. We work closely with the front office and across SFM to provide solutions across many areas of quantitative finance.

Job Overview
We are seeking a Quantitative Research Analyst to partner with our macro portfolio managers to generate insights that drive investment strategies and improve desk performance. This role emphasizes rigorous research, testing, and interpretation of results. Success requires creativity in scoping research problems, discipline in testing hypotheses, and the ability to communicate findings clearly to investment decision-makers.

Major Responsibilities
•Solidify and Enhance Price Pressure Toolset
•Replace legacy Matlab and C# infrastructure with modern, Python-based architecture
•Extend algorithm to allow for the incorporation of additional variables such as z-score, positioning, etc
•Assist with desk strategy and worfklows
•Analyze large datasets (market, economic, alternative) to extract actionable insights that inform trading strategies
•Contribute to desk P&L and risk reporting infrastructure and reporting
•Work with our PM teams on quantitative macro research projects
•Build out Signal Research and Order-Generation Infrastructure
•Partner with broader quant team to build out signal back-testing and data analysis infrastructure
•Build visualization tools for signal, research, and back-testing
•Automate research and order generation workflows

What We Value
•Bachelor’s Degree in a STEM field. Advanced degree preferred.
•5+ years of relevant work experience in a front office quantitative role
•Exposure to G7 fixed income markets.
•Strong proficiency in Python and standard libraries (Pandas, NumPy, Scikit-learn, etc.).
•Experience designing and testing predictive models with large financial datasets.
•Familiarity with model governance practices.
•Excellent communication skills targeting technical and non-technical audiences.

We anticipate the base salary of this role to be between $200,000-250,000. In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus.

In all respects, candidates need to reflect the following SFM core values:
Smart risk-taking // Owner’s Mindset // Teamwork // Humility // Integrity