Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Sign up for Jobbird
An error occurred while opening the sign-up page. Please try again.

Loading window...

Forgot my password
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Log out
Unfortunately, something went wrong while signing out. Please try again.

Loading window...

Job application sent
Something went wrong while logging in. Please try again.
Something went wrong while signing up. Please try again.

Loading window...

logo
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Filters
Filters
Location and distance
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Jobs posted from
Salary from (per month)
Filters
How our sorting works

The order in which job vacancies are displayed is determined by a composite score based on the following factors:

  • Keyword Relevance: How well your search terms match the vacancy details. We prioritize matches found in the job title, followed by job requirements, location names, and educational levels. Matches within general employer information or the organization's name carry a lower weight.
  • Commercial Prioritization (Premium Jobs): Vacancies paid for by employers ('Premium' or 'Sponsored') receive a ranking boost and will appear higher in the search results.
  • Recency (Date Relevance): Newer vacancies are prioritized. The relevance score of a vacancy is reduced by half once the posting is older than 30 days.
  • Proximity (Distance Relevance): Vacancies located closer to your search location are ranked higher. For vacancies located more than 30 km from the search center, the relevance score is halved.
The final ranking is established by multiplying all these individual factors to calculate the total relevance score.

S

Quantitative Researcher

Search Elements MENA City of London
new


Show Recently closed jobs

    S

    Quantitative Researcher

    Search Elements MENA City of London
    new
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    Job description

    Location: London / New York (Hybrid/Remote options available)

    Compensation: Highly competitive base salary + performance-linked bonus structure

    Overview

    We are currently partnering with a premier systematic investment firm to identify an exceptional Machine Learning Quantitative Researcher. In this role, you will join a specialized research team dedicated to developing next-generation quantitative trading strategies.

    This position offers the opportunity to leverage extensive computational resources and robust data infrastructure to focus exclusively on greenfield research. You will be tasked with applying advanced machine learning methodologies to complex, unstructured datasets to identify and capture new sources of alpha in global financial markets.

    Key Responsibilities

    • Design, develop, and deploy advanced machine learning models (including Deep Learning, Reinforcement Learning, and modern sequence models) to forecast asset price volatility and directional movement.
    • Conduct rigorous, empirical research across diverse, large-scale datasets to extract commercially viable trading signals.
    • Partner closely with senior portfolio managers and quantitative developers to seamlessly transition research models into high-performance, production-ready trading systems.
    • Continuously monitor, evaluate, and optimize model performance in live trading environments.

    Basic Qualifications

    • Education: Ph.D. Or Master’s degree in Machine Learning, Computer Science, Physics, Applied Mathematics, Statistics, or a closely related quantitative discipline from a top-tier academic institution.
    • Programming Expertise: Advanced proficiency in Python and C++ within a Linux/UNIX environment.
    • Technical Stack: Extensive practical experience with leading machine learning frameworks (e.g., PyTorch, JAX, or TensorFlow).
    • Research Experience: A demonstrated track record of designing and implementing complex machine learning architectures to solve rigorous, data-heavy problems. Note: Prior experience within the financial services or quantitative trading sector is not a prerequisite.
    • Execution: Strong analytical capabilities with a demonstrated focus on the commercial application and real-world deployment of theoretical models.


    About the employer

    Search Elements MENA
    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


    Vacancy actions

    Save as favorite
    Share vacancy
    Or apply later


    City of London England

    Jobs

    • Search for jobs
    • Jobs per location
    • Jobs per job profession
    • Jobs per employment
    • Jobs per educational attainment

    Jobbird

    • Switch to different region
    • Terms and Conditions
    © 2026 Jobbird