Quantitative Engineer

About the role

To build solutions that better automate tasks within the Investment Risk organization. The Investment Risk team operates independently to provide objective oversight to senior executives, to portfolio management teams, and to external parties such as Fund boards. Investment Risk identifies, measures, and manages a wide array of investment-related risks across all portfolios using advanced analytics and qualitative methods. Investment Risk focuses on portfolio construction to raise awareness of unintended risks that may detract from strategy objectives. This Quantitative Engineer role sits within the Strategy & Execution team, which serves an important function within the Investment Risk group. Strategy & Execution drives change management, manages projects with enterprise leaders, and builds software to help strengthen the impact of the Investment Risk team. This role will help redefine the standard of automated solutions used to support the team's mission, ensuring seamless risk monitoring and alignment with organizational frameworks and objectives. Requirements of the Role: Degree in a quantitative subject such as Statistics, Economics, Financial Engineering, Computer Science CFA, FRM/PRM and/or MBA (Finance) are desirable Experience with AI and scripting applications used to enhance efficiency Experience as a team player helping to contribute to technology project deliverables Experience working in cloud-based environments such as AWS is a plus Experience in applying machine learning techniques is a plus Not mandatory, but it would be helpful to have previous experience with vendor software commonly used in asset management: Barra, RiskMetrics, FactSet, Charles River, Aladdin, Bloomberg, Morningstar, Macrobond, Compustat, Worldscope, DataStream Intermediate coding skills with extensive hands-on experience in R, Python, SQL or other languages used to engineer large datasets Good understanding of financial instruments and a familiarity with international financial markets (e.g.- ., Equities, Fixed Income, FX, Derivatives) Fundamental understanding of core machine learning concepts is preferred Effectively operate within a team-oriented and collaborative environment Strong interpersonal skills, with the ability to build relationships across all levels of an organization and to drive stakeholder consensus Intellectually curious with attention to detail Superior problem-solving capability Highly motivated self-starter with ability to operate autonomously and independently Comfort working at the intersection of business, data, and technology, translating needs into practical solutions Ability to communicate process and automation concepts clearly to both technical and non‑technical stakeholders Good time management and able to work under occasional time- pressure Comfortable working within a project management team and managing multiple concurrent deliverables Full Time / Part Time Full time Worker Type Employee Job Exempt (Yes / No) Yes Workplace Model Pursuant to Invesco's Workplace Policy, employees are expected to comply with the firm's most current workplace model, which as of October 1, 2025, includes spending at least four full days each week working in an Invesco office. This reflects our belief that spending time together in the office helps us build stronger relationships, collaborate more easily, and support each other's growth and development. 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. Invesco's culture of inclusivity and its commitment to diversity in the workplace are demonstrated through our people practices. We are proud to be an equal opportunity employer. All qualified