Description

You will manage data acquisition, ingestion, and lifecycle to support model development and enterprise standards.

This role is hybrid.

Responsibilities

• Build and maintain complex ETL jobs, frameworks, and automated data extraction tools for development and production.
• Design data models, including entity relationship diagrams and dimensional models, using industry standard tools.
• Develop metadata, data lineage, and documentation to ensure compliance with data governance and quality standards.
• Translate complex technical designs and data requirements into actionable solutions for non-technical business partners.
• Support development and testing teams by resolving data issues and providing escalation support for complex problems.

Required Skills

• 5+ years of experience in advanced data analytics or predictive modelling.
• Proficiency in Python, SQL, SAS, and Excel VBA.
• Experience with Linux/Unix operating systems and the Microsoft Azure platform for analytics.
• Hands-on experience with statistical methods and libraries such as SPSS, SAS, or R.
• Practical knowledge of financial services, including commercial/retail lending, stress testing (CCAR, DFAST), and model governance.
• Strong quantitative background with a Graduate degree in Statistics, Mathematics, Economics, Computer Science, Actuarial Science, Finance, or Engineering.
• Competency in Microsoft Office tools, including Excel, VBA, Word, and PowerPoint.

Preferred Skills

• Experience with automated data extraction tool development.
• Background in model governance and regulatory compliance.

Key Skills

Education

Any Graduate