Quantitative Analyst, Solutions Research & Analytics
Invesco
- Location
- London, London
- Work model
- On-Site
- Level
- Mid
- Posted
- 13h ago
Skills
About this role
As one of the world’s leading independent global investment firms, Invesco is dedicated to rethinking possibilities for our clients. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world. If you're looking for challenging work, intelligent colleagues, and exposure across a global footprint, come explore your potential at Invesco.
Job Description
We have an outstanding benefits package which includes: Company-provided healthcare A competitive annual leave allowance Flexible working options, including hybrid working arrangements Generous pension provisions Income protection Health and wellness benefits Volunteering days Enhanced parental leave Life insurance Your role: As part of the Portfolio Construction and Engineering team, you will work alongside some of the best quantitative researchers and technologists to help evolve our investment capabilities. You will be responsible for performing research, managing data, and developing APIs that will be used to power the investment process along with our flagship portfolio construction and analytics platform – Invesco Vision®. The role will allow for significant opportunities for creativity and innovation.
Key Responsibilities
Helping construct multi-asset and single asset portfolios using advanced asset allocation and portfolio construction techniques Building high performance computing algorithms, infrastructure and APIs Researching and building prediction and forecasting methods based on both classical statistical techniques as well as ML based techniques including Agentic workflows leveraging Generative AI Helping translate investment frameworks from various segments of the market (i.e. cash flow driven investing, liability driven investing, insurance capital efficient portfolio construction) into tangible investment and client engagement tool L everaging advanced optimization techniques to create optimal portfolio solutions for internal and external stakeholders Employing multi-period simulation tools to project and optimize performance in the context of flows and optionality Integrating third party risk models in various portfolio construction exercises Designing and maintaining procedures and tools that make data management and research more efficient Working closely with other quantitative and technology teams in the firm in leveraging best practices from a financial theory and technological perspective. Formulating new ideas for research that will help enhance frameworks and tools Following academic research and industry trends to constantly incorporate best practices What you can bring: Solid understanding of standard financial analytics and metrics with focus on Pension and Insurance related analytics Experience with matching adjustment calculations and pension regulations will be a plus Excellent knowledge of statistics and optimization Some experience using third party risk models such as BarraOne or Axioma will be a plus Advanced degrees in quantitative disciplines such as engineering, finance, operations research, or computer science is required Progress towards CFA designation preferred Strong ability to learn and translate abstract principles into systematic algorithmic representations Disability Confident Scheme: Applicants who opt in to the Disability Confident Scheme and meet the criteria for the role will be offered an interview. We are committed to providing an inclusive recruitment process for all candidates who make an application. By opting-in to this scheme, applicants will be disclosing that they have a disability solely for the purpose of the Disability Confident Scheme. The Disability Confident Scheme only guarantees an interview – it does not automatically mean that applicants interviewed will gain employment with Invesco at that time. To apply through the Disability Confident