Quantitative Analyst, Portfolio Engineering – Analytics

. Help construct multi-asset and single-asset portfolios using advanced asset allocation and portfolio construction techniques .

Posted 10/7/2026full-timeUnited StatesMid-LevelSenior💰 $130,000 - $135,000 per yearWebsite

Tools & technologies

PythonPyTorchScikit-LearnSQLTensorflow

Key responsibilities & impact

Help construct multi-asset and single-asset portfolios using advanced asset allocation and portfolio construction techniques
Build high-performance computing algorithms, infrastructure, and APIs
Research and build prediction and forecasting methods using classical statistical and machine learning techniques, including Generative AI
Translate investment frameworks into tangible investment and client engagement tools
Leverage advanced optimization techniques to create optimal portfolio solutions for internal and external stakeholders
Employ multi-period simulation tools to project and optimize performance in the context of flows and optionality
Integrate third-party risk models in portfolio construction exercises
Design and maintain procedures and tools that improve data management and research efficiency
Collaborate with quantitative and technology teams to leverage financial theory and technology best practices
Formulate research ideas to enhance frameworks and tools
Follow academic research and industry trends to incorporate best practices

What you’ll need

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
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

Comp & perks

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