Data Engineer / Data Scientist

*Applicants must have work rights in Singapore, no visa sponsorship available. This is a 6-8 week (data engineer) / 6 months (data scientist) contract based fully-onsite in Singapore.

Requirement description

Our client, a global consulting firm is working with a regional bank and is seeking experienced Data Engineers AND Data Scientists to strengthen its deposit analytics capabilities, establish and optimise the data architecture and pipelines required to support deposit analytics, machine learning and pricing decision-making.

The Data Engineer will build efficient, reusable data pipelines and data models to enable reliable data processing and support the development of deposit flow and customer elasticity models, as well as AI-enabled decision-support tools.

The Data Scientist will develop machine learning models to analyse customer behaviour, assess deposit flow patterns and measure customer price elasticity , while contributing to AI-enabled decision-support tools.

This is a fully onsite role based in Singapore.

Data Engineer

Duration: 6-8 weeks

Key Responsibilities:

• Design and implement data architecture to support deposit analytics and machine learning use cases
• Build efficient, scalable and reusable data pipelines to ingest, transform and process large datasets
• Develop and optimise data models to support deposit flow analysis, customer elasticity modelling and pricing analytics
• Prepare and structure data for downstream machine learning and AI engineering applications
• Ensure data quality, consistency, reliability and accessibility for analytical use cases
• Collaborate with Data Scientists and banking stakeholders to understand data requirements and deliver fit-for-purpose data solutions
• Document data architecture, pipeline logic and data models to support maintainability and future development

Data Scientist

Duration: 6 months

Key Responsibilities:

• Develop and implement machine learning models using Python to analyse deposit flows, customer behaviour and deposit pricing sensitivity
• Build customer elasticity models to assess how changes in interest rates and product pricing influence deposit balances and customer decisions
• Analyse large datasets to identify trends, patterns and insights that inform deposit pricing and product strategies
• Develop and contribute to AI-enabled decision-support tools to support product and pricing decisions
• Translate analytical findings and model outputs into actionable business recommendations for stakeholders
• Collaborate with data engineers and banking stakeholders to ensure data quality, model performance and effective implementation

Requirements:

• Minimum 4-5 years experience in data science, machine learning, data engineering, data architecture or a closely related technical role
• Strong proficiency in Python and experience developing machine learning models using large datasets
• Experience developing data models and preparing large datasets for machine learning use cases
• Strong technical problem-solving skills and an understanding of data quality and pipeline optimisation
• Banking, financial services or pricing analytics experience is highly preferred
• Strong communication skills and the ability to work directly with client stakeholders