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Quantitative Analyst, Portfolio Engineering Analytics
Develop portfolio construction analytics, APIs, forecasting methods, and machine learning models to support investment capabilities at Invesco. Apply quantitative research, optimization, simulation, and data engineering across portfolio and client solutions.
संयुक्त राज्य
मैसाचुसेट्स
न्यूयॉर्क$1,30,000 – $1,35,000 / वर्ष
ऑन-साइटपूर्णकालिकमध्य स्तरवरिष्ठआवश्यक भाषा: अंग्रेज़ीडेटा विश्लेषकविवरण
- Support construction of multi-asset and single-asset portfolios through advanced asset allocation and portfolio construction methods
- Develop high-performance computing algorithms, infrastructure, and APIs
- Research and implement prediction and forecasting approaches using statistical methods, machine learning, and Generative AI
- Convert investment frameworks into practical tools for investment teams and client engagement
- Apply advanced optimization methods to develop portfolio solutions for internal and external stakeholders
- Use multi-period simulations to forecast and optimize performance under flows and optionality
- Incorporate third-party risk models into portfolio construction analyses
- Create and maintain processes and tools that strengthen data management and research productivity
- Partner with quantitative and technology teams to apply financial theory and technology best practices
- Develop research concepts that improve existing frameworks and tools
- Monitor academic research and industry developments to bring relevant best practices into the work
आवश्यकताएँ
- An advanced degree in a quantitative field such as engineering, finance, operations research, or computer science
- Working knowledge of established financial engineering methods
- Strong capabilities in statistics and optimization
- Excellent programming ability, preferably in Python
- Experience developing and deploying machine learning models in financial applications, especially neural network architectures such as LSTM, CNN, and transformers, is advantageous
- Proficiency with scikit-learn, TensorFlow, and PyTorch for neural network modeling
- Experience handling and transforming large datasets, preferably with SQL
- Ability to learn complex concepts and express them as systematic algorithms
- Experience with third-party risk models such as BarraOne or Axioma is advantageous
- Progress toward the CFA designation is preferred
- Ability to prioritize responsibilities and manage time to maximize impact on the investment process
- Exceptional attention to detail and a habit of validating and triangulating results
- Strong interpersonal and collaborative partnership skills
- Commitment to producing high-quality work
लाभ
- Flexible paid time off
- Hybrid working arrangement
- 401(k) match equal to 100% of the first 6% contributed, plus a discretionary supplemental contribution
- Health and well-being programs
- Parental leave
- Employee stock purchase plan
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