- Collaborate with other members of the investment team on predictive analytics, cross-sectional and time series analysis and natural language processing related projects.
- Apply machine learning and statistical techniques to build models derived from financial and alternative data.
- Deliver insights to team members using data visualization tools such as proprietary dashboards.
- Deploy and maintain production models on cloud infrastructure.
- Contribute to data sourcing strategy supporting our prediction efforts, such as evaluating new sources of data for investment signals.
- Prepare research reports that communicate the processes and outcomes of investment data science projects.
Relevant Experience and Qualifications
- Technical academic backgrounds (Data Science, Statistics, Mathematics, Operations Research, Physics, Econometrics, Financial Engineering).
- Work experience in finance, asset management, consulting, equity research.
- Programming skills: Python, R, SQL, Cloud Engineering on AWS or GCP.
- Experience working with large datasets, including classification, regression and other predictive modelling techniques.
- Empirical, detail-oriented mindset.
- A strong track record of working both independently and within a small team.
- Strong problem-solving skills, critical thinking, intellectual curiosity and passion.
Candidates with the following will have an advantage:
1. Practical experience developing quantitative investment strategies would be a plus.
2. Finance related qualifications such as the Chartered Financial Analyst.