Deposits Area Product Team - Quant Analytics Senior Associate

The Finance Decision Optimization team is a group of product, analytics, and engineering experts who support the development of forecasting models used to drive strategic decisions across CCB Finance.

As a Quant Analytics Senior Associate, with the Deposits Area Product team, you will use multi-faceted analytics to support the end-to-end development deposit pricing model – a framework used to help support deposit pricing decision making.

• Partner with the business modeling team to develop and refine statistical models, while continuously evaluating their performance and effectiveness. Validate that production results comply with business requirements and expected results.
• Leverage advanced analytics and predictive modeling to guide the deposit pricing team in identifying and executing optimal pricing strategies.
• Translate business demands to technical requirement documents and collaborate with technology teams. Work closely with end-users/data product owners during the UAT phase and perform testing to ensure new functionality meets end user requirements.
• Take a leadership role and set strategic direction and thought leadership in support of the Area Product Owner.
• Effectively manage multiple tasks and priorities in a fast-paced environment while maintaining responsiveness to ad-hoc requests.

• Strong problem solver with excellent analytical, critical thinking, communication, organizational, and technical skills, with proven ability to collect, organize, and analyze significant amounts of information while maintaining attention to detail and accuracy.
• 3+ years of experience at a financial institution or consulting firm in one or a combination of the following areas: corporate finance, banking, treasury, data analytics, or quantitative modeling. Preference to those with experience dealing with large scale data projects.
• Proficiency in business analytics tools (SQL, SAS, Python, R) or programming languages to perform data analytics and drive business outcomes. Experience with Databricks, Streamlit, and AWS Cloud environments is preferred.
• Able to communicate effectively with a variety of technical peers including data engineering and quantitative modeling teams and ability to translate data into concise and actionable recommendations.