Quant Researcher
Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Oct 20, 2026.
Who We Are
Founded in Modena, Italy, in 2016, Axyon AI marks ten years of applying artificial intelligence to investment management. We develop AI-powered solutions for asset managers and hedge funds, leveraging proprietary AI and deep-learning technology to analyse financial time series, identify predictive signals, and support systematic investment strategies.
Our quantitative researchers, data scientists, and engineers work together to address the challenges of applying AI to financial markets, from evaluating signals to building and refining investment strategies. For a Quantitative Researcher, this offers the opportunity to develop practical research skills and see how their work contributes to the solutions we deliver.
We support professional development through a dedicated learning budget and offer flexible working arrangements within an inclusive, collaborative team.
What We’re Looking For
We are looking for an early-career Quantitative Researcher with practical experience in systematic equity research and the ability to take ownership of well-defined research projects.
You will join our Quant Research team and contribute to the evaluation and improvement of systematic equity strategies, working closely with colleagues across research, data, and engineering.
The role requires the ability to apply sound research judgement, work with limited day-to-day supervision, and communicate findings and limitations clearly.
Location: Modena, Italy
What You’ll Be Doing
Contribute to the research and development of systematic equity strategies:
Take ownership of well-defined research projects, from formulating hypotheses and preparing data to evaluating results and documenting conclusions.
Research and engineer features, assess predictive signals, and evaluate their robustness through appropriate statistical testing and out-of-sample analysis.
Evaluate how signals translate into implementable equity strategies, considering portfolio construction, risk exposures, turnover, and transaction costs.
Analyse strategy performance and investigate the sources of returns and risk.
Maintain and improve Python research tools, backtesting workflows, and reproducible analytical pipelines.
Work with data and engineering colleagues to integrate validated research into reliable workflows.
Present research findings, methodological choices, and limitations to internal stakeholders.
What You Need
Previous hands-on experience in a professional quantitative research environment, with evidence of substantive contributions to research projects.
Practical experience taking a defined research question through data analysis, validation, and interpretation of results.
Strong Python programming skills and experience with SQL.
Working knowledge of systematic equity investing, with practical experience in at least one of: signal validation, performance attribution, risk modelling, or portfolio construction and optimisation.
Ability to identify methodological issues, propose next steps, and progress independently while seeking input when needed.
English proficiency at B2 level or above, both written and spoken.
Intellectual curiosity and a strong interest in quantitative investment research.
Nice to Have
Experience or familiarity with one or more of the following is considered a plus:
Familiarity with Git-based version control workflows and Docker-based development environments.
Experience with feature engineering for financial machine learning.
Familiarity with transaction cost modelling and the assessment of strategy turnover and implementation constraints.
What You’ll Gain
Gross annual salary of €32,000-€36,000, commensurate with experience.
A long-term employment opportunity, with the contractual arrangement tailored to your profile and aimed at permanent employment.
A benefits package including welfare benefits, health insurance, and access to psychological support services.
A learning budget for courses, conferences, and books.
Flexible working hours and a remote-working policy.
A collaborative work environment with modern facilities and equipment, and regular opportunities for knowledge sharing and professional development
If you are curious about quantitative finance, eager to learn, and excited to work in a fast-growing AI company, we would love to hear from you!