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# Head of Machine Learning – Quantitative Hedge Fund – New York, NY


 
Head of Machine Learning (ML) – Quantitative Hedge Fund
Are you an innovative Machine Learning leader with a proven track record in quantitative research and algorithmic model development? We are seeking a Head of Machine Learning to drive ML strategy, research initiatives, and model production for a leading quantitative hedge fund in New York, NY. This is an exceptional opportunity to shape the future of systematic trading and contribute to cutting-edge portfolio optimization through advanced data science and machine learning methodologies. If you excel in fast-paced, intellectually demanding environments and have a passion for breakthrough innovation, this role offers the platform to create meaningful impact.
Lead ML Innovation for a High-Performance Quant Fund in New York
A top-tier quantitative hedge fund in New York, NY is looking for a Head of Machine Learning to lead the development and deployment of scalable ML-driven investment strategies. The ideal candidate will have deep expertise in predictive modeling, time-series forecasting, high-frequency data analysis, and machine learning frameworks used in the financial markets. You will collaborate closely with quantitative researchers, portfolio managers, and data engineers to build models that enhance trading performance, reduce risk, and unlock alpha. If you thrive at the intersection of finance, ML innovation, and advanced research, this is your opportunity to influence critical investment decisions and build cutting-edge machine learning systems from the ground up.
Key Responsibilities of the Head of Machine Learning – Quantitative Hedge Fund
Machine Learning Strategy & Vision:
As the Head of Machine Learning, lead the development and execution of an advanced ML roadmap that aligns with the fund’s investment strategy. Identify opportunities to leverage artificial intelligence, predictive analytics, and automation to strengthen trading and portfolio decision-making.
Model Development & Optimization:
Oversee end-to-end model lifecycle—including research, design, back-testing, validation, deployment, and ongoing optimization. Ensure machine learning models deliver measurable alpha generation, reduce risk, and support high-frequency or systematic trading strategies.
Data Infrastructure & Innovation:
Collaborate with data engineering teams to build scalable data pipelines and ensure high-quality data ingestion from diverse sources. Drive innovation by evaluating new tools, ML frameworks, and emerging technologies relevant to quantitative finance.
Cross-Functional Collaboration:
Partner closely with quantitative researchers, portfolio managers, and software engineers to integrate ML-driven insights into investment strategies. Provide actionable guidance that enhances model interpretability and improves execution efficiency.
Leadership & Team Building:
Build, mentor, and lead a world-class machine learning research team. Foster a culture of experimentation, high performance, and continuous learning while promoting best practices in ML, data science, and quant research methodologies.
Performance Tracking & Continuous Improvement:
Monitor model performance in live trading environments and ensure continuous calibration. Utilize performance metrics and rigorous validation frameworks to refine algorithms and maximize predictive accuracy.
Risk Management & Compliance:
Ensure all machine learning projects adhere to compliance frameworks and risk management guidelines. Implement robust model governance processes to maintain transparency, auditability, and regulatory adherence.
Technical Excellence & Documentation:
Establish coding standards, version control processes, and thorough documentation for research and production models. Promote reproducibility, data integrity, and security across ML operations.
Stakeholder Communication:
Present model performance updates, research findings, and strategic recommendations to senior leadership, stakeholders, and investment committees. Communicate complex ML concepts in a clear and data-driven manner to support strategic decision-making.
What the Client is Looking for in You
As the Head of Machine Learning at a quantitative hedge fund, the client seeks an exceptional leader with deep expertise in machine learning, quantitative research, and data-driven decision-making. The ideal candidate is a strategic innovator who thrives in fast-paced and highly analytical environments, capable of transforming complex data into actionable trading insights and measurable investment outcomes.
Proven Leadership in Machine Learning & Quantitative Finance
The client is searching for a seasoned Head of Machine Learning with a strong track record of designing, deploying, and optimizing machine learning models within quantitative trading environments. You should have demonstrated success in leading high-impact ML initiatives, working with large-scale financial datasets, and delivering predictive models that generate alpha. Experience in managing the full lifecycle of ML and AI model development is highly valued.
Strategic Thinker with a Vision for Innovation
As the Head of Machine Learning, you must have the ability to define a long-term ML strategy that aligns with the firm’s investment objectives. The client values individuals who constantly explore emerging technologies, stay ahead of industry developments, and identify new opportunities to enhance portfolio performance. You should be adept at converting complex concepts into scalable solutions that drive competitive advantage.
Exceptional Technical Expertise
You bring deep hands-on experience in advanced ML techniques—such as deep learning, time-series forecasting, reinforcement learning, and natural language processing—and proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks. The ideal candidate has strong statistical reasoning, understands market microstructure, and can lead rigorous experimentation to refine model accuracy and performance.
Ability to Build and Lead High-Performing ML Teams
Leadership is at the core of this role. The client is looking for someone who can attract, develop, and mentor world-class ML and data science talent. You should excel at fostering a collaborative, research-driven culture while empowering teams to innovate and execute efficiently. Experience leading cross-functional teams—including Quants, Data Engineers, and Software Developers—is highly desirable.
Data-Driven Decision Maker
The client seeks someone who is highly analytical, comfortable with ambiguity, and driven by measurable outcomes. You should be able to evaluate model performance, interpret complex results, and make informed decisions backed by data and experimentation. Strong communication skills are essential for presenting insights to senior management and investment committees.
Strong Stakeholder Collaboration & Communication
As the Head of Machine Learning, you will work closely with portfolio managers, quantitative researchers, and business leadership. The client values clear communicators who can simplify advanced ML concepts and build alignment across teams. Your ability to provide transparency and present data-backed insights will be essential to gaining support and investment in new initiatives.
Commitment to Compliance & Risk Management
Finally, the client is seeking a leader who understands the importance of model governance, compliance frameworks, and responsible AI practices. You should have a proactive approach to mitigating operational, regulatory, and reputational risk across machine learning projects.
FAQs About the Role – Head of Machine Learning – Quantitative Hedge Fund
1. What are the key responsibilities of the Head of Machine Learning in this role?
As the Head of Machine Learning, you will lead the development and implementation of machine learning models that support quantitative investment strategies. You will oversee the full ML model lifecycle—from research and data preparation to deployment and performance optimization. Additionally, you will collaborate with quantitative researchers, portfolio managers, and engineering teams to integrate ML-driven insights into systematic trading and portfolio decision-making.
2. What qualifications and experience are required for this position?
The ideal candidate should have extensive experience in machine learning, quantitative finance, and model development. Strong proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), statistical modeling, and time-series forecasting is essential. Previous experience working within a hedge fund, quantitative trading firm, or financial research environment is highly preferred. A master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related quantitative discipline is ideal, but equivalent experience may also be considered.
3. What leadership qualities are essential for this role?
The client is looking for a Head of Machine Learning who can combine technical excellence with strong leadership capabilities. You should be able to mentor and guide a team of ML researchers and data scientists, foster a collaborative culture, and communicate complex findings clearly to stakeholders. An innovative mindset, strategic thinking, and the ability to manage multiple high-impact research initiatives simultaneously are key to success.
4. What challenges can I expect in this role?
You can expect challenges such as working with large, complex, and sometimes noisy datasets; ensuring that models are both predictive and scalable in live trading environments; and maintaining compliance and risk transparency across ML projects. The role demands rigorous testing, experimental discipline, and continuous model refinement to ensure consistent alpha generation in competitive markets.
5. How does this role impact the hedge fund’s performance and long-term goals?
The Head of Machine Learning will play a critical role in shaping investment decisions and driving competitive advantage through machine learning innovation. Your ability to build high-performing predictive models will directly influence trading success, portfolio performance, and the firm’s capacity to capitalize on market opportunities.
6. What is the work environment like at the firm?
The firm operates in a fast-paced, intellectually stimulating environment that values research, innovation, and continuous learning. Collaboration, transparency, and ownership are core cultural principles. As the Head of Machine Learning, you will have the opportunity to influence team culture and help build a world-class machine learning function within the organization.
What Remuneration Can You Expect from This Job?
As the Head of Machine Learning at a quantitative hedge fund in New York, NY, you can expect a highly attractive compensation package designed to reward exceptional technical and strategic leadership. Compensation in this field is structured to reflect the high-impact nature of machine learning contributions to trading performance and firm profitability.
1. Base Salary
The base salary for a Head of Machine Learning in a top-tier hedge fund typically ranges from $250,000 to $500,000+ annually, depending on the firm’s size, fund performance, and your level of experience. Elite quantitative trading firms may offer even higher base salaries to secure top machine learning talent.
2. Performance-Based Bonuses
In addition to the base salary, most hedge funds offer substantial annual performance bonuses tied to measurable outcomes such as alpha generation, model performance, and trading profitability. Performance bonuses commonly range from 50% to 200%+ of the base salary, with top performers earning significantly more based on results.
3. Profit Sharing & Investment Incentives
Many firms include profit-sharing or revenue participation models that allow the Head of Machine Learning to share directly in the performance of ML-driven investment strategies. This aligns individual performance with firm-wide financial success, providing significant upside potential.
4. Equity, Partnership, or Deferred Compensation
Depending on the structure of the fund, compensation may include equity, deferred compensation, or partnership units. These incentives reward long-term model performance and encourage alignment with the firm’s long-term strategic goals.
5. Benefits & Executive Perks
A competitive benefits package may include:

Comprehensive health, dental, vision, and wellness benefits
Retirement or 401(k) plan with employer contributions
Paid time off, personal days, and flexible hybrid work models where applicable
Annual learning budget for conferences, research, certifications, or ML education programs

Top firms also offer perks such as business-class travel for conferences or executive offsites, advanced equipment/technology, and performance-based offsite retreats.
6. Relocation Assistance & Signing Bonus
For highly qualified candidates, the firm may offer relocation support or signing bonuses. Signing bonuses for Head of Machine Learning roles can range from $25,000 to $200,000, depending on candidate experience and the speed of hiring required.
Total Earnings Potential
When combining base salary, annual bonuses, profit-sharing, and long-term incentives, total compensation for a Head of Machine Learning at a leading quantitative hedge fund can range from $600,000 to several million dollars annually, particularly in high-performing funds or with consistent alpha contributions.
How to Apply
If you are an innovative and strategic leader with a proven track record in machine learning, quantitative research, and data-driven model development, we invite you to apply for the Head of Machine Learning position at a leading quantitative hedge fund in New York, NY. This is a rare opportunity to influence investment decisions, drive ML-led alpha generation, and shape the future of systematic trading at a high-performing fund.
To apply, please submit your resume and a detailed cover letter outlining your experience in:

Machine learning model development and deployment
Quantitative finance or algorithmic trading (preferred)
Leading high-performing ML teams
Driving measurable improvements in model accuracy, predictive insights, or portfolio performance

Be sure to highlight achievements such as alpha generation, performance improvements through ML innovation, and successful implementation of machine learning frameworks at scale. Showcase your ability to bridge the gap between technical ML execution and strategic investment impact.
This role offers significant influence, high visibility, and the ability to make a measurable impact on the firm’s performance. Apply today to take the next step in your career as the Head of Machine Learning at a world-class quantitative hedge fund in New York, NY.
For more information or to explore similar executive-level opportunities in quantitative finance, visit our Data Analytics & ML Executive Search Firm page.
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Head of Machine Learning | Quantitative Hedge Fund Jobs | Machine Learning Leadership | Quant Trading & Data Science | ML Strategy & Innovation | Model Development & Deployment | Financial Data Science Leadership | New York ML Jobs