ST Asset Management Ltd – Data Modeller

Project Title: Data modelling for Financial forecasts

Background:

Our department provides applications to the company to perform Financial forecasts, as well as to enable the company to gain insights useful for timely and accurate decisions. We are hiring a Data Modelling intern for building and improvement of existing forecasting models.

Objectives:

As an intern, you will be responsible for:

1) Development and enhancement of existing forecasting models, using the application of statistics and machine learning, with the help of languages such as Python and R. You will have the chance to have a hands on exposure to forecasting models, such as S&P 500, Forex, interest rates and stock index forecasting models, build base on machine learning models such as multilayer perceptron (MLP), recurrent neural network (RNN) and convolutional neural network (CNN) , ARIMA.  You are required to constantly improve on the accuracy and the relevance of our forecasting model. Of which the results would then be used for investment decision makings. You will also have opportunities to present to internal stakeholders.

2) Creating tools for managing and presenting data. This includes data visualization techniques, data analytics and data processing. You will be provided opportunities to work closely with the end user in order to structure and present data according to their specifications and needs.

Special Knowledge / Skills Required:

1) Proficiency in at least one data analytics/processing language, such as R/Python.

2) Prior knowledge of time series and regression modelling is required.

3) Prior knowledge of Machine Learning models, such as the multilayer perceptron (MLP), recurrent neural network (RNN) and convolutional neural network (CNN), is not necessary, but preferred.

4) Have an interest in finance and economics.

5) Confidence in public speaking in small groups.

Above all, you should have a strong work ethic and enthusiasm for learning, as well as good communication skills.

Hardware & Software provided:

Visual Studio 2017, Microsoft SQL Server 2016, R, Python, Tableau.