Internship - Pattern Recognition and Prediction – (6 months)
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 225 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.
Internship - Pattern Recognition and Prediction - (6 months)
You will integrate the Finance-core development team within the Technology and Operations Unit based in Geneva. The team is at the heart of the core banking platform and is in charge of accounting and position keeping systems among others.
Those systems are very data centric and handle large volume of operations and transactions on a daily basis. The team also provides business users with Manual-Entries web application which is used to manually record banking transactions.
The goal of this internship is to analyze and categorize manually recorded transactions using pattern recognition algorithms that you will implement.
The second step is to predict the transactions that need to be generated and suggest them to the user within Manual-Entries web application.
YOUR ROLE
Lead the data analysis with all stakeholders including the Operation teams, business analysts, the development team and data-office AI experts.
Implement pattern recognition and prediction algorithms using the appropriate technical stack.
Integrate the transaction suggestion feature within Manual-Entries application backend & frontend.
Active collaboration with teams to understand the business and propose solutions.
Follow Agile (Scrum) methodology.
YOUR PROFILE
Graduated (or currently pursuing a degree) in Data Science, Computer Science, Mathematics or a related field.
Good knowledge of SQL python and Java.
Previous experience or project involving machine learning is a plus.
Collaborative, team player with the ability to work independently.
Ability to take ownership of tasks from the beginning through to conclusion.
Meticulous, proactive and able to multi-task.
Fluent in French.
Resident in Switzerland or willing to relocate to Switzerland.
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.
Internship - Pattern Recognition and Prediction – (6 months)
Internship - Pattern Recognition and Prediction - (6 months). The goal of this internship is to analyze and categorize manually recorded transactions using pattern recognition algorithms that you will implement. Implement pattern recognition and prediction algorithms using the appropriate technical ...
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