Join our Commercial & Investment Bank Analytics team to help identify and implement solutions using data and AI to generate actionable insights. This role offers a unique opportunity to apply your knowledge and experience in data and AI to help business operations uncover operational insights that drive efficiency and business performance. 

As a Data/AI Analyst in the Commercial & Investment Bank Analytics team, you will be an integral part of a dynamic Data Analytics team supporting the bank’s Digital and Platform Services function. This role involves applying data science knowledge and experience to identify, design, and implement key solutions that generate transparency and insights in business operations to support executive management. 

Job Responsibilities: 

Identify AI application areas for insight generation and data management Lead solutions development and implementations that support insight generation Lead prompt engineering setup and execution for AI implementations Serve as a subject matter expert on data analysis tools, techniques, and concepts 

Required Qualifications, Capabilities, and Skills: 

3+ years of experience in data analysis, solution development, and implementations within financial services or technology/AI consulting Hands-on experience solving complex business problems using data Proficiency in programming languages such as R, Python, and SQL Competency in data architecture, LLM, and AI concepts Strong communication skills Team player with a strong work ethic and professionalism Demonstrated experience in working with multiple stakeholders in a complex data environment Willingness and curiosity to learn new technologies, tools, and business operations 

Preferred Qualifications, Capabilities, and Skills: 

Knowledge of data preparation processes for graph databases Experience/knowledge of RAG architecture to support conversational AI implementations Knowledge/Experience with Graph RAG Familiarity with data analytics toolsets such as Qlik Sense, Tableau, SQL, and Alteryx Familiarity with data architecture and data management