CA

Quantitative Developer Python - Alpha Signals

Capital Fund Management (CFM) paris Posted 29 Sep 2026 Closing: 29 Oct 2026
Permanent Hybrid
€60 - €100

Role Description & Overview

In collaboration with the Research teams, the Front Prediction team develops and maintains the prediction models (alpha signals) used to make decisions for our automated trading systems.

Overview

The Front Prediction team develops and maintains predictive models used to make decisions for our automated trading systems.

Responsibilities

  • Integrating and validating new predictive models within our Python decision platform
  • Designing and building prediction workflows (simulation and production), including Machine Learning components
  • Developing and optimizing applications for distributing prediction models calculations
  • Continuously improving the suite of non-regression and pre-production control tools to accelerate the Research process
  • Monitoring the production of prediction applications, liaising with the support teams

Qualifications

  • You have a scientific degree and at least 5 years' experience in a similar role in market finance (Asset Management - Hedge Fund: Equity / Future / High Frequency Trading)
  • You have knowledge and experience in the field of Machine Learning
  • You are keen to ensure an excellent level of code quality, testing and user support
  • You have an excellent command of Python and Pandas
  • You are a team player and have a good command of English
  • Linux is your natural environment

Equal Opportunities Statement

We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success. CFM is a signatory of the Women Empowerment Principles.

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Key Details
  • Date Posted: 29 Sep 2026
  • Location: paris
  • Employment: Permanent
  • Workplace: Hybrid
  • Specialism: Finance, Informatique & Technologie
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Capital Fund Management (CFM)
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