Our client - a tier-one global multi-strategy hedge fund - is looking to hire a talented Machine Learning Quantitative Researcher to join a very successful, highly collaborative systematic investment pod in the US or London.
This hire will work closely with an industry-leading PM and team on researching and deploying cutting-edge systematic equity strategies with a primary focus on Machine Learning.
What you'll be doing:
- Working alongside the PM on ML-based alpha generation, research/analysis and backtesting for systematic equity strategies.
- Developing and deploying ML methods for signal generation and portfolio optimization.
- Use scientific methods and ML techniques to harness datasets in order to build strong predictive models which will be deployed into the investment process.
What you will bring:
- 3+ years of experience working in a Quantitative Research/Development capacity in a systematic trading environment (buy-side preferred), with product experience in Equities (preferably stat arb)
- Excellent research and programming skills in Python and Python-based tools and libraries.
- Masters or PhD in a STEM field.
- 3+ years of experience applying ML to real-world data sets.
- Commercial experience with NLP and GNN.
To discuss this outstanding opportunity in full, please apply below or reach out to Elaine Bunyan at ebunyan@paragonexecutive.com
We look forward to hearing from you!
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