At Schwab, the Treasury Analytics & Reporting team is looking to transform manual processes into automated, robust solutions while delivering comprehensive reporting and analysis to support treasury operations and decision-making.
Requirements
- 1+ years of hands-on experience in Python programming and data analysis
- Experience with data visualization tools, Web App and Tableau experience is a plus
- Experience with process automation and workflow optimization
- Proficiency in data extraction, transformation, and analysis techniques
- Familiarity with agile development and project management methodologies
- Knowledge of SQL, database concepts, and ETL processes
- Familiarity with version control systems (GitHub) and development best practices
Responsibilities
- Working closely with treasury stakeholders and team members to understand business needs and requirements for reporting and automation solutions.
- Performing data extraction, transformation, and analysis using Python and other analytical tools like Big Query, Power BI, etc.
- Creating interactive dashboards and visualizations to support treasury reporting needs.
- Supporting data modeling, process optimization, and ensuring deliverables meet both functional and operational requirements.
- Assisting in planning, scheduling, and coordination of technical activities related to treasury automation projects.
- Ensuring solutions align with best practices and following established development methodologies.
- Collaborating with technology teams and other departments to ensure timely delivery of high-quality analytical solutions.
Other
- Bachelor's degree in Finance, Economics, Computer Science, Engineering, or related field
- 2+ years of professional experience in financial analysis, treasury operations, or data analytics
- Strong oral, written, and interpersonal skills for interacting throughout all levels of the organization
- Ability to interpret key financial trends and metrics and leverage them for actionable insights
- Critical-thinking skills with ability to identify process improvement opportunities
