You will be attached to the Investment Strategy Department, who is responsible for setting up asset allocation strategies, framework and models, and also coming up with asset allocation decisions that contributes to the insurance funds total returns.
You are required to assist the Investment Strategy Department to build and test a machine learning based sentiment model, which will contribute to the overall tactical asset allocation models and process.
Key responsibilities include:
- Execution of Python Codes (including documentation and analysis of the results)
- Maintain existing Python scripts on the processing of large volume of news data for labelling of population selection
- Setup and execution of Python Codes for developed sentiment models on the large volume of news data
- Post processing of the sentiment model outputs for the purpose of calibrating and building a sentiment index
- Analysis of the sentiment model outputs including the interpretation and documentation of the results
- Data Quality Review of Labelled Historical News Articles; Careful reading of a sample of the labelled historical financial news articles to verify that the logic of the labelling was adhered to
Qualifications - External
- Bachelor or Master Degree in Computer Sciences, Maths or equivalent
- Finance background will be advantageous
- Hands on experience with Python programming language including the available packages for statistical analysis and data manipulation
- Knowledge of statistical methods including in depth understanding of various regression methods
- Familiarity with Machine Learning and Natural Language Processing Methods
- Some understanding of macroeconomics and the financial markets is preferred