Data Scientist (AI Applications)

CAPITALMASTER PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Capitalmaster Pte Ltd, a fintech company in Singapore, is seeking a Data Scientist (AI Applications) to join the technology team. You will analyse data, support data modelling, and evaluate AI-enabled product features to drive product insights.

You will develop reports and dashboards, collaborating with product and engineering teams to translate data into actionable business decisions. You will explore new AI technologies, perform exploratory analyses, and ensure data quality across structured

Responsibilities

• Collect, clean, process and analyse structured and unstructured data for business and product requirements.
• Perform data validation and quality checks to ensure data accuracy and consistency.
• Conduct exploratory and statistical analysis to identify trends, patterns and actionable insights.
• Support data modelling, feature engineering and evaluation of machine-learning or AI-enabled product features.
• Develop reports, dashboards and data visualisations to support analysis and decision-making.
• Use Python, SQL and other analytical tools for data extraction, processing and analysis.
• Collaborate with product and technical teams on data requirements, model evaluation and AI-related enhancements.
• Evaluate new data science, machine-learning and AI technologies for potential business applications.

Tools

Python

SQL

Job description

About the Company

Capitalmaster Pte Ltd is a financial technology company specialising in stock analysis software and AI-enabled software applications. We develop digital solutions to enhance financial analysis, data-driven insights, system automation and product innovation.

We are looking for a Data Scientist (AI Applications) to join our growing technology team. The role focuses on data analysis, data modelling and the evaluation of AI-enabled product features, working closely with product and technical teams.

Key Responsibilities

• Collect, clean, process and analyse structured and unstructured data for business and product requirements.
• Perform data validation and quality checks to ensure data accuracy and consistency.
• Conduct exploratory and statistical analysis to identify trends, patterns and actionable insights.
• Support data modelling, feature engineering and evaluation of machine-learning or AI-enabled product features.
• Develop reports, dashboards and data visualisations to support analysis and decision-making.
• Use Python, SQL and other analytical tools for data extraction, processing and analysis.
• Collaborate with product and technical teams on data requirements, model evaluation and AI-related enhancements.
• Evaluate new data science, machine-learning and AI technologies for potential business applications.