Lombard Odier Group
Quantitative Analyst Intern Multi-Asset
Skills
15 days ago
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Important information
Contract type:
Permanent
Location:
Geneva, Switzerland
Work mode:
Onsite
Published on:
6 October 2026
What they need
A career at Lombard Odier means working for a renowned global wealth and asset manager, with a strong focus on sustainable investing. An innovative bank of choice for private and institutional clients, our independently owned Firm is one of the best-capitalised banking groups in the world, managing close to CHF 300 billion and operating from over 25 offices across 4 continents.
With a history spanning over 230 years, Lombard Odier is an investment house providing a comprehensive offering of discretionary and advisory portfolio management, wealth services and custody. We also offer asset management services and investment strategies through Lombard Odier Investment Managers and provide advanced banking technology to other financial institutions.
“Rethink Everything” is our philosophy – it is at the heart of everything we do. We have grown stronger through more than 40 financial crises by rethinking the world around us to provide a fresh investment perspective for our clients.
Lombard Odier Investment Managers (“LOIM”) is the asset management business of the Lombard Odier Group. To continue the long-standing collaboration between EPFL and Lombard Odier, the Multi-Asset group at LOIM is seeking a Geneva-based:
Quantitative Analyst Intern Multi-Asset
As a Quantitative Analyst within the Multi-Asset group, you will focus on enhancing LOIM’s research environment alongside other scientists and engineers. Your work will be instrumental in improving the research lifecycle using scientific methods to develop sophisticated investment models for various markets and instrument types.
YOUR ROLE
Your mission will be to thoroughly research an original topic related to eg alpha-generating strategies, risk modelling, etc which might lead to an academic publication in a peer-reviewed journal.
Past and potential subjects include but are not limited to: The use of implied volatility indices for volatility forecasting, Cross-asset trend-following, Cross-asset carry, Allocation models for quantitative investment strategies, High-frequency correlations across futures markets, Machine-learning allocation models for asset allocation signals, risk factors & estimators
YOUR PROFILE
Computer programming and related IT skills necessary to the implementation of quantitative strategies
- Python
- Ideally MySQL, GIT, Tableau
Solid background in statistical measures and analysis
Strong problem solving and quantitative skills; high degree of intellectual curiosity
Hard-working, diligent and eager to learn in an intellectual and collaborative environment
Able to be persistent, effective and collaborative to solve issues
Well-organized, detail-oriented, able to focus in a dynamic environment and able to work under deadline
Ability to balance/optimize finding own solutions and asking for help
While we do not require extensive experience for this role, prior experience working with an Asset Management organisations or a similar role is a plus
Our Maison’s DNA is defined by five core values. Excellence drives us to be the best at what we do, while Innovation fuels our progress. Respect underpins every interaction, and Integrity shapes our actions. Together, we are One Team, united in serving our clients with unwavering dedication.
As a responsible and supportive employer, we promote a diverse and inclusive work environment for our employees and candidates. Diversity, Equity and Inclusion are woven into the fabric of our Maison’s DNA, and we strive to ensure that our employees can fulfill both their personal and professional aspirations by encouraging internal mobility and individual upskilling programs. We firmly believe that building Diverse Teams contributes to our successes and to deliver on this, we actively embed Diversity, Equity and Inclusion in our business strategy.
It is an exciting time to join our Teams. All applications will be handled in the strictest confidence.
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