Quantitative Portfolio Manager

Posted 13 Days Ago
Be an Early Applicant
2 Locations
In-Office or Remote
Mid level
Fintech • Financial Services
A pioneering fintech and algorithmic trading firm
The Role
AlgoQuant Asset Management is seeking Portfolio Managers to develop and execute algorithmic trading strategies in crypto markets, focusing on risk-adjusted returns and leveraging proprietary infrastructure. Candidates should possess a strong quantitative research background.
Summary Generated by Built In

Portfolio Manager – AlgoQuant Asset Management

Reports to the CIO

Location: London, New York or Dubai (Fully Remote)

About AlgoQuant Asset Management

AlgoQuant Asset Management is an ambitious, high-performing, and pioneering multi-strategy crypto asset manager. For over five years, we have operated as a proprietary trading firm, making tactical allocations to both internal and external quantitative trading teams.

In 2024, Michael Ashby joined as CEO, bringing expertise from leading Point72’s digital assets division across quant, venture, and macro trading. With a strengthened executive team, we are transitioning into an investment management firm, managing external capital while leveraging our technology, risk management expertise, and deep market experience.

At AlgoQuant, we believe in the power of both internal and external teams, casting a wide net for new ideas, identifying world-class talent, and diversifying our alpha sources.

Our PM group is highly experienced in selecting alpha strategies and in portfolio construction. We expect a strong understanding of risk-adjusted returns and running a variety of algorithmic trading strategies.

The Role: 

AlgoQuant is seeking highly skilled and ambitious Portfolio Managers (PMs) with a proven track record of success in algorithmic trading. As a PM, you will be responsible for developing, optimizing, and executing systematic trading strategies within the crypto markets. You will have access to our institutional-grade infrastructure, deep liquidity, and significant capital allocations to maximize returns. We are open to candidates from both crypto-native and traditional finance backgrounds who demonstrate strong research and trading capabilities.

Who We Are Looking For

We consider two types of candidates for this role:

  1. Experienced Crypto Portfolio Managers
    • A successful +1.5-year track record in crypto markets with demonstrable returns.
    • Currently running a strong portfolio but looking for access to more capital, better infrastructure, and superior financial terms.
  2. Traditional Finance (TradFi) Portfolio Managers
    • A strong track record in traditional financial markets with impressive risk-adjusted returns.
    • Limited or no exposure to crypto markets but seeking a transition into the space.
    • We will consider high performing sub-PM’s working on a successful trading desk, looking to take the lead with independent research and portfolio construction.

Key Responsibilities

  • Develop, implement, and manage high-performing algorithmic trading strategies.
  • Conduct independent research using big data and market microstructure data to seek alpha and identify trading signals.
  • Optimize strategies for execution, scalability, and efficiency in live trading environments.
  • Manage portfolio risk, ensuring robust risk-adjusted returns and adherence to AlgoQuant’s risk management framework.
  • Work collaboratively with internal teams to leverage proprietary data, trading infrastructure, and execution capabilities.
  • Determine the structure of your team and work with the Chief People Officer to build a high-performing quant research team if additional support is needed.
  • Stay at the forefront of market developments, leveraging new technologies, data sources, and analytical techniques to maintain competitive advantage.

Key Qualifications

  • A minimum of 1.5+ years of successful track record in crypto or traditional finance trading, with strong annual P&L contributions.
  • Strong quantitative research background with expertise in statistical modeling, machine learning, and market microstructure.
  • Proficiency in Python for research and strategy development, with experience handling large datasets.
  • Deep understanding of risk management, portfolio construction, and optimization techniques.
  • Ability to work autonomously while also collaborating with AlgoQuant’s broader research, trading, and technology teams.
  • Strong leadership skills with the ability to mentor and manage a team if required.

What We Offer

  • Access to significant trading capital to scale your strategies.
  • Cutting-edge infrastructure, including research platforms, execution algorithms, and deep liquidity access.
  • Competitive financial terms and a performance-driven compensation structure.
  • A collaborative, high-caliber environment with top-tier talent in quantitative finance and crypto markets.
  • The opportunity to lead your own trading strategy while leveraging AlgoQuant’s institutional framework.

How to Apply

If you meet the qualifications and are looking to join a world-class trading environment, we invite you to apply. Please submit your CV and a brief overview of your trading track record, strategy focus, and past performance.

Top Skills

Machine Learning
Python
Statistical Modeling
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The Company
14 Employees
Year Founded: 2019

What We Do

At AlgoQuant, we're building the future of digital asset management; grounded in rigorous research, world-class technology and a relentless focus on performance.

We began as a proprietary trading firm, developing sophisticated algorithmic strategies and operating in some of the most complex and fast-moving markets. That DNA remains at our core, but today we are evolving into a fully remote, globally distributed Investment Management business. This transformation reflects a broader ambition: to scale our edge, deliver institutional-grade results, and set new standards for the industry.

Our quantitative environment is built to empower innovation, combining vast data capabilities, disciplined model development, and highly automated execution. Risk is embedded in every layer of our thinking, with robust measurement, control, and scenario analysis integrated into our systems and decision-making. Technology is not just a tool for us, it’s a core competency and a competitive advantage.

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