Corporate Treasury Analytics Lead

Responsibilities

• Sources, extracts, and consolidates data from external sources and core treasury systems.
• Builds and maintains internal data sources and curated datasets in Databricks to support Treasury teams.
• Develops SQL queries, APIs, and ETL processes to move and transform large datasets.
• Designs and implements automated workflows (Python, SQL, Power Automate) to streamline treasury reporting and reduce manual processes.
• Collaborates with cross-functional teams to integrate analytics into treasury processes and reporting.
• Serves as a bridge between Treasury and data engineering teams by developing reusable data products in Databricks.
• Drives innovation in analytics platforms and data visualization tools.
• Ensures model governance, documentation, and validation in line with regulatory expectations.
• Supports stress testing and regulatory submissions (e.g., CCAR, DFAST, LCR, NSFR).

Qualifications and Education Requirements

• Bachelor’s degree in Analytics, Finance, Mathematics, Statistics, or related field.
• 8+ years of experience in analytics, treasury, or risk management within a financial institution.
• Strong knowledge of regulatory frameworks and model governance standards.

Key Competencies

• Strong understanding of treasury functions and financial risk management.
• Proficiency in programming languages and tools (e.g., Python, R, SQL, MATLAB).
• Experience with data visualization platforms (e.g., Tableau, Power BI).
• Excellent communication and stakeholder engagement skills.
• Ability to manage multiple projects and deliver high-quality results.