Quantitative Analyst, Portfolio Engineering & Analytics

Your Role As part of the solutions research and analytics 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. You will be responsible for: · 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 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 tools · Leveraging 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 The experience you bring: · Advanced degree in quantitative disciplines such as engineering, finance, operations research, or computer science is required · Solid understanding of standard financial engineering techniques · Excellent knowledge of statistics and optimization · Excellent programming skills (preferably in Python) · Some experience in developing and deploying machine learning models, with a focus on neural network architectures like LSTM, CNNs and transformers in financial contexts will be positive · Proficient in programming scikit-learn, TensorFlow and PyTorch for neural network modeling · Experience managing and manipulating large data sets (preferably in SQL) · Strong ability to learn and translate abstract principles into systematic algorithmic representations · Some experience using third party risk models such as BarraOne or Axioma will be a plus · Progress towards CFA designation preferred Skills / Other Personal Attributes Required: · Ability to prioritize work and allocate time efficiently to maximize impact to investment process · Very strong attention to detail with internal drive to sanity check and triangulate results · Strong interpersonal and partnership skills · Passion to deliver excellent work 130k-135k Full Time / Part Time Full time Worker Type Employee Job Exempt (Yes / No) Yes Workplace Model The above information on this description has been designed to indicate the general nature and level of work performed by employees within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. The job holder may be required to perform other duties as deemed appropriate by their manager from time to time.