The Emerald Recruiting Group
A
global multi-strategy hedge fund
is seeking a
Cross-Asset Quantitative Researcher
to develop and enhance models that drive investment decisions across equities, fixed income, FX, and commodities. This is a high-impact role for a researcher who thrives at the intersection of
mathematics, markets, and machine learning —someone who doesn’t just build models, but shapes how capital is deployed.
You’ll join a collaborative team of PMs, quants, and technologists who live and breathe data. The environment is meritocratic, fast-moving, and wired for scale—where good ideas get capital and results matter more than titles.
What You’ll Do
Research, design, and implement
systematic alpha strategies
across multiple asset classes and time horizons.
Develop predictive models using advanced statistical, econometric, and ML techniques.
Analyze market microstructure and cross-asset relationships to uncover
relative-value and macro-driven opportunities.
Collaborate with Portfolio Managers, Data Engineers, and Technologists to bring research into production.
Conduct
signal validation, risk analysis, and performance attribution
for existing and new strategies.
Work with large, complex datasets from both traditional and alternative sources; identify new data streams that can drive alpha.
Optimize execution algorithms, portfolio construction, and hedging techniques.
Document research and maintain reproducible, well-structured code and analysis pipelines.
What You Bring
3–8 years
of experience in quantitative research or trading within a hedge fund, bank, or proprietary trading environment.
Advanced degree (PhD or Master’s) in a quantitative discipline such as
Applied Math, Physics, Statistics, Computer Science, or Financial Engineering.
Deep understanding of
financial markets and instruments
across asset classes.
Proficiency in
Python
(preferred), C++, or similar; familiarity with high-performance computing and data visualization tools.
Demonstrated ability to translate theory into practical trading models and signals.
Experience with
alpha research, risk modeling, portfolio optimization, and execution analytics.
Creative, detail-oriented, and relentless in testing, validating, and refining ideas.
Why It’s Worth a Conversation
Work alongside
elite quants and PMs
in one of the most data-driven, high-performance environments in finance.
Access to cutting-edge infrastructure, massive data sets, and institutional-scale research resources.
Competitive
payout structure
and real opportunity to turn ideas into deployed capital.
Culture that rewards intellectual honesty, collaboration, and measurable impact.
#J-18808-Ljbffr
global multi-strategy hedge fund
is seeking a
Cross-Asset Quantitative Researcher
to develop and enhance models that drive investment decisions across equities, fixed income, FX, and commodities. This is a high-impact role for a researcher who thrives at the intersection of
mathematics, markets, and machine learning —someone who doesn’t just build models, but shapes how capital is deployed.
You’ll join a collaborative team of PMs, quants, and technologists who live and breathe data. The environment is meritocratic, fast-moving, and wired for scale—where good ideas get capital and results matter more than titles.
What You’ll Do
Research, design, and implement
systematic alpha strategies
across multiple asset classes and time horizons.
Develop predictive models using advanced statistical, econometric, and ML techniques.
Analyze market microstructure and cross-asset relationships to uncover
relative-value and macro-driven opportunities.
Collaborate with Portfolio Managers, Data Engineers, and Technologists to bring research into production.
Conduct
signal validation, risk analysis, and performance attribution
for existing and new strategies.
Work with large, complex datasets from both traditional and alternative sources; identify new data streams that can drive alpha.
Optimize execution algorithms, portfolio construction, and hedging techniques.
Document research and maintain reproducible, well-structured code and analysis pipelines.
What You Bring
3–8 years
of experience in quantitative research or trading within a hedge fund, bank, or proprietary trading environment.
Advanced degree (PhD or Master’s) in a quantitative discipline such as
Applied Math, Physics, Statistics, Computer Science, or Financial Engineering.
Deep understanding of
financial markets and instruments
across asset classes.
Proficiency in
Python
(preferred), C++, or similar; familiarity with high-performance computing and data visualization tools.
Demonstrated ability to translate theory into practical trading models and signals.
Experience with
alpha research, risk modeling, portfolio optimization, and execution analytics.
Creative, detail-oriented, and relentless in testing, validating, and refining ideas.
Why It’s Worth a Conversation
Work alongside
elite quants and PMs
in one of the most data-driven, high-performance environments in finance.
Access to cutting-edge infrastructure, massive data sets, and institutional-scale research resources.
Competitive
payout structure
and real opportunity to turn ideas into deployed capital.
Culture that rewards intellectual honesty, collaboration, and measurable impact.
#J-18808-Ljbffr