Senior Quant Research Analyst, Machine Learning
1 month ago
Senior Quant Analyst, Machine Learning/AI
Financial Technology industry leader has unique opportunity for a Senior Quant Analyst with AI/Machine Learning experience to join their growing, NY based team in a full time, hybrid role. This individual will join a team of technology, finance, and data analytics experts building portfolio trading models powered by alternate data analysis and Machine Learning models. In this role you will build, validate, back test, and deploy algorithmic trading strategies that generate alpha for asset managers. Candidates need hands on experience with traditional machine learning, deep learning, Bayesian statistics, ensemble methods, clustering, and parametric and non-parametric statistics, as well as knowledge of standard financial pricing and portfolio models. This is an ideal role for a highly motivated individual to build and mentor a team in a highly collaborative, team environment.
Required Skills and Experience:
- 5+ years of experience applying AI and machine learning strategies to build successful quantitative trading solutions for institutional investors.
- Experience researching, developing, and productionizing successful trading strategies across asset classes for US markets.
- Deep knowledge of financial model development using statistical/econometric methods and machine learning techniques.
- Hands on Python software development. Hands on coding experience with C++ is a plus.
- Experience with LLM including Llama 3, opensource AI model.
- Experience productionizing non-linear machine learning models in Python.
- Experience creating ML/AI driven quant research to create next generation alpha strategies portfolio construction.
- Knowledge of portfolio models, financial economics, and financial time-series analysis
- Advanced degrees in Quantitative Finance, Statistics, Applied AI, Data Science or similar.
- Knowledge of numerical methods and optimization techniques
- Experience leading and mentoring a junior team is required.
- Collaborative team player with strong communication, documentation, and presentation skills.
- Experience using unstructured data and alternate data analysis is highly preferred.
- The ideal candidate should be comfortable working in a modern, distributed architecture, SDLC, and hands on Python coding skills.
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