Quantitative Analyst, Portfolio Engineering & Analytics

Invesco

New York (NY)

Hybrid

USD 130,000 - 135,000

Full time

13 hours ago
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Benefits offered by this job

Flexible paid time off
Hybrid work schedule
401(K) matching up to 6%
Health & wellbeing benefits
Parental Leave benefits
Employee stock purchase plan

Job summary

Invesco is expanding its Solutions Research and Analytics team in New York. You will work with top quantitative researchers to develop APIs powering Invesco Vision, focusing on multi-asset portfolio construction, predictive modeling, and advanced optimization.

You’ll build scalable infrastructure and collaborate across teams to translate research into client-facing tools, employing ML techniques including neural networks in financial contexts.

Qualifications

  • 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 with ML models in finance (e.g., LSTM, CNNs, transformers).

Responsibilities

  • Help construct multi-asset and single-asset portfolios using advanced asset allocation techniques.
  • Build high-performance computing algorithms, infrastructure and APIs.
  • Research and build prediction and forecasting methods using classical statistics and ML.
  • Translate investment frameworks into tangible investment tools.
  • Leverage optimization to create portfolio solutions for internal and external stakeholders.
  • Integrate third-party risk models into portfolio construction exercises.
  • Design and maintain data management and research tools to improve efficiency.
  • Collaborate with other quantitative and technology teams to share best practices.

Skills

Python
Statistics
Optimization
ML Modeling
Large Data Handling
Communication

Education

Advanced degree in quantitative discipline

Tools

Python libraries (scikit-learn)
TensorFlow
PyTorch
SQL

Job description

About Invesco
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.

About Invesco
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.
What’s in it for you?
Our people are at the very core of our success. Invesco employees get more out of life through our comprehensive compensation and benefit offerings including:

  • Flexible paid time off
  • Hybrid work schedule
  • 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution
  • Health & wellbeing benefits
  • Parental Leave benefits
  • Employee stock purchase plan
Job Description
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
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 applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender, gender identity, sexual orientation, marital status, national origin, citizenship status, disability, age, or veteran status. Our equal opportunity employment efforts comply with all applicable U.S. state and federal laws governing non-discrimination in employment.
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