Responsibilities:
- Utilize financial and other data to create or improve predictive models
- Develop and/or leverage leading-edge statistical and machine-learning models to enhance the research and development systems
- Create algorithms to monetize the predictive signals.
- Apply statistical techniques for time-series measurement / estimation and prediction
Further Qualifications:
- NLP Competence: Deep understanding of Natural Language Processing methods required for analyzing unstructured text data.
- Large Language Models (LLM): Experience working with LLMs necessary for developing state-of-the-art quant strategies informed by vast amounts of textual information
- Programming: Strong proficiency in Python needed due to its prevalence in statistical modeling tasks relevant to both signal generation & strategy implementation (must also have working knowledge of SQL and other common data science toolkits such as R and Spark)
- Strong data science modeling intuition and feature engineering creativity
- Must have graduate degree in a STEM subject (preferably a PhD)
- Any specific experience with datatsets such as medical transcripts and broker notes would be a plus but not required
- Open to consider candidates coming from tech or finance industries
