Internship - Next-gen Identity Matching Using Vector Search
vor 1 Woche
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 - Next-Gen Identity Matching using Vector Search
Join our CRM innovation stream to explore and implement a modern approach to identifying duplicate person records using vector similarity search. This internship offers a unique opportunity to work on cutting-edge technologies in the field of data quality and entity resolution.
YOUR ROLE- Analyze the current duplicate detection logic and identify its limitations.- Design and implement a proof-of-concept using vector search techniques (e.g., nearest neighbor search).- Evaluate and compare vector database solutions such as Redis Vector and Elasticsearch.- Develop APIs and services using Java with Quarkus or Spring Boot.- Document architectural decisions and contribute to DevSecOps pipelines.- Collaborate with data engineers, CRM developers, and business analysts to refine the solution.
YOUR PROFILE- Enrolled in a Master’s degree in Computer Science, Data Engineering, or a related field.- Strong interest in Java development and microservice frameworks.- Strong interest in vector databases, similarity search, or machine learning.- Knowledge of Redis, Elasticsearch, or other vector search engines will be highly considered.- Curious, analytical, and eager to explore innovative approaches to data problems.- Fluent in English and French. Other language is a plus.- Resident in Switzerland or willingness to relocate.
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.
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