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Responsibilities
Responsibilities:
- Elevate predictive modeling standards in statistical arbitrage of traded funds.
- Build a world-class modeling workflow turning massive financial datasets into accurate market-prediction models.
- Uncover untapped signals in the fixed-income section of the traded universe.
- Develop and optimize calibration and benchmarking frameworks.
- Build and implement best practices for data preparation and dataset generation pipelines.
- Prototype and release novel predictive architectures, especially time-series models.
- Collaborate with software engineers and traders across the full inception-to-deployment cycle.
Requirements:
- Approximately 3+ years professional experience in quantitative research or financial data development.
- Fluency in mathematics and statistics.
- Experience with valuation and hedging of fixed-income instruments.
- Full ML stack experience: data generation
- calibration
- real-life validation & monitoring.
- Strong Python skills for data wrangling and numerical programming.
- Solid computer science fundamentals.
- A scientific, inquisitive, hands-on mind
- not purely academic.
- Willingness to work on-site in Copenhagen (1 day/week remote).
- MSc or PhD in Physics, Engineering, Computer Science, Mathematics, or Economics preferred (top-100 globally ranked university preferred).
This job post is closed.