Quantitative Researcher - Equity Statistical Arbitrage
$960,000–$1,080,000 year
On-siteCopenhagen, Capital Region, Denmark
Copenhagen, Capital Region, DenmarkOn-siteFull Time$960,000–$1,080,000 yearDoctorate Or Professional DegreeSmall
Full TimeDoctorate Or Professional DegreeSmall
Job Summary
Develop and optimize calibration frameworks and data preparation pipelines to transform massive financial datasets into predictive mathematical models. Prototype novel time-series architectures and release them within hours to validate against real-life market movements. Bridge advanced machine learning with market microstructure to build scalable, risk-managed portfolios focused on uncovering untapped signals in the fixed-income section. Engage on a nitty-gritty technical level with software engineers and traders to drive change across the broader modeling strategy.
Required Qualifications
- at least three years of professional experience
- Fluency within mathematics and statistics
- Experience working with financial data, in particular valuation and hedging of fixed-income instruments
- Experience working with the full Machine Learning stack from data generation through model calibration and real-life validation and monitoring
- Programming experience with Python, in particular data-wrangling and numerical programming
- Proficiency with computer science fundamentals
- A scientific and inquisitive mind
- evidence of real-world application and implementation experience
- solid development skills and basic CS knowledge
- comfortable in a practical, coding-focused environment
Desired Qualifications
- PhD from a top-tier university
- candidates from physics, engineering, or computer science backgrounds
- experience in the valuation and hedging of fixed-income instruments
- experience working with 'out-of-core' datasets
- Experience working with tools like PyTorch, Tensorflow, XGBoost and/or Catboost
- Programming experience with languages like C# and C/C++
- PhD or MSc degree in engineering, physics, computer science, mathematics or economics
- significant practical experience (e.g. applied projects, coding, data work)
- some software development exposure within finance
- Financial experience, particularly working with financial data
- experience in valuation and hedging of fixed-income instruments
- candidates from other areas of finance (e.g. risk)
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