Quantitative Data Analyst and Developer for Investment Solutions
1 semana atrás
About the Job
We are building a new team to support our European Investments unit at Nordea Asset Management. The team will work closely with quant and analysts from the Investment unit in the Nordics to develop and maintain our core platform for data flows, mathematical models, and AI solutions for our investment boutiques.
About This Opportunity
You will be working closely with Quant Developers and Analysts in Copenhagen to develop and maintain our core platform for data flows, mathematical models, and AI solutions for our investment boutiques. The primary role of the new team is within core platform development, maintenance, and support, but we work as a single model development value stream across Portugal and Denmark, collaborating on defining both what to do and how to do it. You will be tasked with understanding our current codebase and taking part in future improvements and new developments within it.
Key Responsibilities
• Develop and support data and model pipelines both for internal use and for investment boutiques.
• Ongoing monitoring, support, and incident management of all flows.
• Taking a proactive role in improving stability and performance of our offerings.
• Help the value stream take over and modernize existing data and model flows.
About the Team
We are an ambitious team that takes ownership of the entire process from idea generation with business stakeholders to deployment and monitoring of live services. The role is based in Oeiras. We collaborate, take pride in our work, and strive towards joint ownership of our codebase.
Requirements
A Master's degree in Engineering or equivalent in Computer Science, Mathematics, Physics, or a related software engineering background. Significant practical experience with Python as a language for core development. Experience with design and development of data and model pipelines. Previous experience with the CI/CD pipelines, particularly within the Atlassian DevOps suite, and scheduling via Airflow are an advantage, but not a requirement.
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