About this role
Join a finance team that supports the Consumer and Business Banking segment with reporting, planning, analytics, and decision-support. In this role, you will help develop and maintain quantitative revenue models and build high-quality datasets that power decisions. You will combine strong technical skills with an understanding of banking products, pricing structures, revenue drivers, and customer behavior. Your work will influence stakeholder outcomes through clear analysis, validated data, and actionable insights.
Job summary
As a Revenue Finance Quantitative Analytics and Data Engineering Analyst within the Consumer and Business Banking Finance team, you will support the development and maintenance of revenue models through quantitative analytics, data engineering, and model implementation. You will prepare and validate large datasets, perform model testing and back-testing, and evaluate model performance to support business objectives. You will apply knowledge of banking products, pricing structures, revenue drivers, and customer behavior to deliver meaningful insights to internal stakeholders, including Finance and Business Management leaders and field finance teams. You will partner across Technology, Finance, and Business teams to translate requirements into analytical solutions and support successful deployment. This role follows a 2:00pm to 11:00pm shift and works in a hybrid in-office model.
Job responsibilities
- Develop and support quantitative revenue models by preparing, validating, and transforming large datasets using Databricks, while ensuring data quality through root cause analysis and issue resolution
- Implement, test, and back-test quantitative models within cloud-based and analytical environments using Python, ensuring model accuracy, robustness, and scalability
- Evaluate model performance, analyze variances, and communicate findings through clear, data-driven recommendations that support business objectives
- Leverage deep understanding of Consumer and Business Banking products, pricing structures, and revenue drivers to support analytical and strategic decision-making
- Conduct advanced analytics and customer behavior deep dives to identify business opportunities, uncover trends, and generate actionable insights for stakeholders
- Partner effectively across Technology, Finance, and Business teams to translate business requirements into analytical solutions and drive successful model deployment
- Prepare and deliver executive-level presentations that effectively communicate complex quantitative, financial, and technical concepts to senior leadership and key stakeholders
Required qualifications, capabilities, and skills
- Bachelor’s degree required
- Advanced proficiency in SQL, Python, and Databricks, with experience in data preparation, transformation, validation, and quantitative model implementation
- Experience working with large, complex datasets and deriving actionable business insights
- Strong analytical and problem-solving skills
- Minimum 2 to 4 years of experience in quantitative analytics, data science, and financial modeling
- Understanding of banking products, pricing structures, revenue drivers, and customer behavior
- Ability to evaluate model performance, analyze variances, and communicate data-driven recommendations
- Strong collaboration skills and ability to partner across Technology, Finance, and Business teams
- Ability to prepare and deliver executive-level presentations communicating complex quantitative, financial, and technical concepts
- Attention to detail, critical thinking, and ability to manage multiple priorities in a fast-paced team environment
- Positive attitude and intellectual curiosity
Preferred qualifications, capabilities, and skills
- Master of Science, Master of Technology, or Master of Business Administration (Finance)
- Experience with cloud-based analytics platforms
- Familiarity with AI tools, Tableau, and Alteryx
- Familiarity with financial modeling