Actively Hiring
AU
Data Scientist - Commodities Trading
Aurex Group
Singapore
Skills:
Data Science
Python
SQL
Statistics
Machine Learning
Job Description
Job Title: Data Scientist - Commodities Trading
Company: Aurex Group
Job Category: Data Science
Roles & Responsibilities:
The role will be working with the regional and global trading teams to provide models and research that is directly used for commercial trading decisions.
We are looking for someone hungry and ambitious who wants to grow with the business and develop this function for the region.
This role will Develop, validate and continuously improve predictive models to support trading and commercial decisions across APAC, covering pricing, market timing, relative value, risk and position management.\= etc
* Degree in Data Science, Statistics, Mathematics, Econometrics, Computer Science, Engineering, Physics or a related quantitative discipline.
* Minimum 5 years' experience developing, testing and implementing predictive models using real\-world datasets.
* Strong proficiency in Python and SQL, with expertise in statistical modelling, machine learning and time\-series analysis.
* Solid understanding of model validation, performance monitoring, calibration, retraining and MLOps.
* Ability to analyse complex, noisy datasets, identify meaningful patterns and distinguish reliable signals from misleading correlations.
* Experience with Azure Databricks, Microsoft Azure or comparable cloud\-based data platforms.
* Familiarity with AI agents and coding assistants, including the ability to assess and validate AI\-generated outputs.
* Strong analytical, problem\-solving and communication skills, with the ability to explain technical findings to trading and commercial stakeholders.
* Self\-motivated and comfortable working independently in Singapore while collaborating with international teams.
Work Location: Singapore, Singapore
Availability: Full time
Requirements
Requirements:
Key Skills: Data Science, Python, SQL, Statistics, Machine Learning
Salary: SGD 120000 - 150000 per yearly