Portfolio Engineering - Internship

Capital Fund Management (CFM); Paris; Hybrid; EUR 13,000 - 20,000; Part time

Job summary

Capital Fund Management (CFM) in Paris, France, invites final-year students for a Portfolio Engineering internship focused on directional optimization. You'll observe constraints, build tools, and help translate research signals into invested positions.

Work with the Directional Portfolio Analytics group to design and compare constraint formulations, monitor their impact on realised positions, turnover and risk, and prepare recommendations for future modelling.

Qualifications

• Final-year student in engineering or MSc in applied mathematics, OR in data science, computer science or finance.
• Solid background in convex optimisation; cvxpy familiarity is a plus.
• Strong Python skills (pandas, NumPy) and write clear, tested code.
• Comfort with real production data and with inconclusive findings.
• Knowledge of portfolio construction and financial markets; duality/sensitivity analysis is a plus.
• Good team practices: Git daily, code reviews, clear writing, direct exchanges with Research and IT.

Responsibilities

• Instrument the optimisation process to observe which constraints bind, and their portfolio consequences over historical data.
• Analyse constraint interactions and quantify impact on realised positions, turnover, risk and performance.
• Design one or two alternative constraint formulations and evaluate them against current ones on real historical portfolios.
• Challenge existing choices and identify formulations that may be artefacts rather than deliberate design.
• Formulate recommendations on how current constraint modelling should evolve.

Skills

Convex optimisation

Portfolio construction

Team practices

Education

Engineering school or MSc in applied mathematics/OR/data science/CS/finance

Tools

cvxpy

Python (pandas, NumPy)

Git

Job description

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Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.
We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

Your Role

The Portfolio Engineering - Directional team, part of the Directional Portfolio Analytics group, plays a central and transversal role within CFM, driven by the values of integrity and excellence. It designs and maintains the internal optimization stack that turns research signals into invested positions. Portfolios are built by solving optimisation problems under many constraints: position, trading, risk, margin and regulatory.

Constraints are meant to shape portfolios in specific ways, but today there is no systematic understanding of which constraints bind and when, how they interact, or whether current formulations produce the intended behavior. When a portfolio behaves unexpectedly, it is hard to tell whether the cause is the signal, the constraints, or their interaction. This is the core of the internship.

Key Responsibilities

• Instrumenting the optimisation process to observe which constraints bind, when, and with what portfolio consequences over historical data.
• Analysing constraint interactions and quantifying their impact on realised positions, turnover, risk and performance.
• Designing one or two alternative constraint formulations, potentially more interpretable or more robust, and evaluating them against the current ones on real historical portfolios.
• Challenging existing choices: identifying formulations that may be historical artefacts rather than considered design, without having to defend them.
• Formulating a recommendation on whether, and how, the current constraint modelling should evolve. "The current formulations are fine" is as valid an outcome as "improvements exist".

Continuously improving the stack:

• Refactoring constraint modelling: organisation, typing, tests and performance.
• Building monitoring dashboards and reusable tooling to improve the quality and observability of portfolio construction.
• Validating each change against real historical portfolios (inputs, active constraints, outputs).

Your Skills

• You are in the final year of an engineering school or an MSc in applied mathematics, operations research, data science, computer science, or finance.
• You have a solid background in convex optimisation; familiarity with cvxpy is a plus.
• You are strong in Python (pandas, NumPy) and write clear, tested, maintainable code.
• You are comfortable with real production data and with messy, inconclusive findings.
• You have a good grasp of, or a strong desire to learn, portfolio construction, and financial markets. Knowledge of duality and sensitivity analysis (shadow prices, Lagrange multipliers) is a plus.
• You follow good team practices: Git daily, code review, clear writing, direct exchanges with Research and IT.

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 .