ZipRecruiter

Log In

1

Hedge Fund Machine Learning Jobs (NOW HIRING)

IQ-EQ

Manager - Hedge Fund Accounting

Iselin, NJ · On-site

You'll manage and train fund accountants, oversee the allocation of daily and monthly activities ... Our learning and development programmes and systems (including PowerU and MyCampus) enable us to ...

IQ-EQ

Manager - Hedge Fund Accounting

Dallas, TX · Hybrid

You'll manage and train fund accountants, oversee the allocation of daily and monthly activities ... Our learning and development programmes and systems (including PowerU and MyCampus) enable us to ...

HedgeServ

Treasury Manager

Raleigh, NC · On-site +1

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... The Treasury Manager is responsible for overseeing treasury operations for our hedge fund and ...

HedgeServ

Treasury Manager

Dallas, TX · On-site +1

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... The Treasury Manager is responsible for overseeing treasury operations for our hedge fund and ...

HedgeServ

Treasury Manager

Dallas, TX · On-site

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... The Treasury Manager is responsible for overseeing treasury operations for our hedge fund and ...

previous page

Showing results 41-60

All JobsHedge Fund Machine Learning Jobs

Hedge Fund Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do hedge fund machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for hedge fund machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the typical projects or challenges a hedge fund machine learning professional may encounter?

As a Hedge Fund Machine Learning professional, you may work on projects involving the development of predictive models for market movements, portfolio optimization, anomaly detection, or automated trading strategies. Common challenges include sourcing high-quality financial data, managing noisy or incomplete information, and ensuring that models remain robust in dynamic market conditions. Additionally, you will often collaborate with portfolio managers, data engineers, and other quant researchers to translate model insights into actionable investment strategies. Overcoming these challenges requires both technical expertise and adaptability, offering significant opportunities for career growth and impact within the fund.

What are the key skills and qualifications needed to thrive in hedge fund machine learning?

To thrive in a Hedge Fund Machine Learning role, you need a strong background in quantitative analysis, statistics, programming (often in Python or R), and machine learning, typically supported by a degree in mathematics, computer science, or a related field. Proficiency with data analysis libraries (like pandas, NumPy), machine learning frameworks (such as TensorFlow or scikit-learn), and experience with financial data sets or platforms is highly valuable. Effective communication, collaboration, and a strong problem-solving mindset are crucial soft skills in this role. These competencies are essential to designing and implementing robust trading models, navigating complex data, and working efficiently in a fast-paced, team-driven environment.

What is a hedge fund machine learning?

A Hedge Fund Machine Learning job involves applying data science, artificial intelligence, and quantitative modeling techniques to improve trading strategies, risk management, and portfolio optimization. Professionals in this role develop and implement machine learning algorithms to analyze financial data, identify patterns, and generate predictive models for market behavior. They work closely with portfolio managers, traders, and quantitative researchers to enhance decision-making and generate alpha. Strong programming skills, expertise in statistics, and knowledge of financial markets are essential for success in this field.

More about Hedge Fund Machine Learning jobs
What cities are hiring for Hedge Fund Machine Learning jobs? Cities with the most Hedge Fund Machine Learning job openings:
What states have the most Hedge Fund Machine Learning jobs? States with the most job openings for Hedge Fund Machine Learning jobs include:
What job categories do people searching Hedge Fund Machine Learning jobs look for? The top searched job categories for Hedge Fund Machine Learning jobs are:
Hedge Fund Machine Learning jobs near you
Infographic showing various Hedge Fund Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners

New York, NY • On-site

Full-time

Medical, Life, PTO

Re-posted 19 days ago

Job description

Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund
Moreton Capital Partners is rapidly expanding and seeking a talented Quantitative Researcher to join us in our Mexico City office to sit alongside a world class, international team.
This is a high-impact role from day one. You'll take full ownership of designing, testing, and refining the next generation of alpha signals in commodity futures, with your models feeding directly into live trading portfolios. Our research is grounded in advanced machine learning, robust testing frameworks, and deep expertise across global commodity markets.
We're looking for someone ready to hit the ground running and available to start immediately. In return, we offer a competitive salary, substantial performance share, comprehensive benefits, incredible work environment and a relocation package to make the move seamless.
Key Responsibilities
  • Research, prototype, and validate systematic trading signals across commodities using advanced ML methods.
  • Design and implement rigorous backtests with realistic frictions, walk-forward validation, and robust statistical tests.
  • Engineer and evaluate novel features from prices, fundamentals, positioning, options data, and alternative datasets (e.g., satellite, weather and global commodity cash pricing).
  • Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods.
  • Develop portfolio construction and optimization techniques and analysis tools to be able to enhance performance and track effects on portfolio execution.
  • Collaborate with developers to transition research into production-ready strategies.
  • Monitor live performance, attribution, and model drift, ensuring continual improvement of the alpha library.

Requirements
  • Masters or PhD in either Statistics, Economics, Computer Science.
  • Strong background in machine learning and statistical modelling (tree-based models, regularization, time-series ML).
  • Proficiency in Python (pandas, NumPy, scikit-learn, XGboost, PyTorch/TensorFlow).
  • Understanding of time-series forecasting, cross-validation techniques, and avoiding look-ahead bias.
  • Academic experience in research and proven ability to translate academic work to production code.
  • Prior exposure to systematic trading or financial modelling.
  • Ability to design experiments, interpret results, and iterate quickly in a research environment.

Bonus points for:
  • Knowledge of commodities (agriculture, energy, metals) or macro markets.
  • Experience with feature engineering on non-traditional datasets (options positioning, weather, satellite).
  • Experience collaborating in version control environments.
  • Familiarity with portfolio optimization, risk parity, or Bayesian model averaging.
  • Publications, Kaggle competitions, or research track record demonstrating applied ML excellence.

Benefits
  • Direct impact: Your alphas will go live into production portfolios, with real capital behind them.
  • Research-first culture: We value deep thinking, novel approaches, and systematic rigor.
  • Close collaboration across a global team.
  • Career growth: Clear trajectory to senior researcher roles as we scale AUM and expand product lines.
  • Attractive compensation: Highly competitive base salary and annual bonus that scales as the business grows.
  • Relocation package to our Mexico City office, along with a competitive benefits offering that includes health and life insurance, a year-end bonus, and generous paid time off.
  • Positive, inclusive and encouraging work environment.

Apply