Conning is looking to leverage quantitative methodologies and machine learning to create optimized performance indicators and develop Fixed Income sector-specific signals to find investment opportunities and gain tradable insights from alternative data.
Requirements
- A foundation in machine learning, deep learning, and NLP (LLM) modeling
- Strong programming skills including Python (Pandas, Tensorflow, PyTorch, Scikit-Learn), and SQL
- Experience and passion for Data Science - machine learning, deep learning, and NLP (LLM)
- Experience working with databases, web-scraping or dealing with alternative data
- Experience with data visualization tools (e.g. Tableau, PowerBi) a plus
- Knowledge in fixed income models and quantitative research a plus
- Master's degree in mathematics, Financial Engineering, Data Science, or related program with experience in mathematical modeling and quantitative methods
Responsibilities
- Implement Automation & Data Solutions: Work with the Quant Research team to build analytical efficiencies and solutions using quantitative methods.
- Data Analytics: Work with the team to expand our data and quant framework.
- Develop tools to load, process, clean, query, analyze data, and work with Technology team to ensure data quality.
- Create accurate documentation for presentation and prosperity.
- Clean & Improve Existing Code: Design, code, test and implement quantitative models, applying data science techniques, in machine/deep learning and NLP.
- Machine Learning / AI: Improve on our existing Machine Learning infostructure.
- This is a combination of data cleaning, finding statistical modeling relationships and implementation of new machine learning models.
Other
- 2-4 years of relevant work experience
- Financial background is a plus
- Strong creative thinking and problem-solving skills; able to decompose complex problems into manageable parts.
- Strong verbal, written, and presentation skills
- Detail oriented and with passion for excellence in all areas of work
