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Quantitative Technology Professional

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Stockholm, Stockholm, Sweden Seb Full time

The SEB xAsset Investment team is seeking a talented Quantitative Technology Professional to join our engineering unit. As a member of our team, you will play a crucial role in developing and implementing cutting-edge technology solutions to support our business goals. Our mission is to create a brighter economic future for our clients through sustainable investments.

We're a leading northern European financial services group offering full-service solutions to private individuals, corporate, and institutional clients. Our asset management company is one of the top players in the Nordic region, managing a wide range of funds and mandates across asset classes.

About the Team:
  • We work closely with portfolio managers and the trading unit as well as other parts of the organization.
  • We strive to create a collaborative and inclusive work environment where employees feel valued and respected.

As a Quantitative Technology Professional, you will:

  1. Evaluate and ensure correct availability for systems in the operational environment.
  2. Manage roadmaps, tasks, and deadlines to prioritize requirements effectively, addressing both short-term and long-term needs.
  3. Serve as a proactive liaison between the different investment and business teams that interact with us.
  4. Drive and encourage adoption of chosen technologies throughout the organization.

Requirements:

  • You have a structured approach and strong delivery focus.
  • You possess demonstrable development experience.
  • You have experience in the asset management or market trading industry, specifically designing, implementing, and managing system frameworks for research and investments.
  • You're skilled in Object-oriented programming and enterprise architecture, with an interest in Cloud-based technologies like GCP and Azure.
  • You're proficient in C# and familiar with LLMs (GPT-4, LAMA 3, Gemini), both prompt and API.
  • Knowledge in Java and Python, as well as data science, is a plus.
  • You have interests in Quantitative/Systematic investment strategies.
  • You hold a relevant academic degree in computer science, engineering, or equivalent.