Data Scientist — Global Services Insights & Analytics, Commercial Banking - Sr. Associate

Job description

Join our Global Services Insights & Analytics team and help turn data into decisions that improve how we operate. You’ll partner with senior leaders, tackle meaningful business problems, and deliver insights that drive measurable outcomes. This is an opportunity to build scalable analytics solutions, strengthen controls, and elevate service and efficiency across Commercial Banking. If you enjoy hands-on data science and clear storytelling, we’d like to hear from you. As a Data Scientist in Global Services Insights & Analytics, you will lead data-driven initiatives that strengthen planning, efficiency, service, and controls within Commercial Banking. You will work closely with senior stakeholders to frame the right questions, design sound analytical approaches, and translate results into practical recommendations. You will combine statistical methods and machine learning with strong business context to deliver actionable insights. You will help build repeatable solutions that scale and improve performance over time. In this role, you’ll help shape how the team measures success and prioritizes improvement opportunities. You’ll balance exploratory analysis with production-ready delivery, and you’ll be expected to communicate clearly to technical and non-technical audiences. You’ll also collaborate across business and functional partners to align on outcomes, timelines, and data requirements. Job responsibilities Lead analytics and insight-generation initiatives using hands-on data science techniquesDevelop experimental frameworks to support data collection and measurementDefine analytics approaches using business knowledge, statistical methods, and machine learning techniquesBuild models and data applications that produce actionable insightsCreate clear visualizations and messaging that simplify complex resultsCollaborate with business and functional stakeholders on analytics initiativesTranslate business needs into well-scoped data solutions and analytical deliverablesPresent insights and recommend next steps to senior stakeholdersRequired qualifications, capabilities, and skills Three years of data science experience (financial services or commercial banking experience preferred)Proficiency in Python, R, and SQLExperience applying statistical methodologies to business problems (for example, experimentation, inference, forecasting, or classification)Experience building machine learning models and translating outputs into actionable recommendationsExperience designing repeatable and scalable data solutionsExperience using analytics tools such as Alteryx or TrifactaExperience working with distributed data environments such as HadoopExperience with data visualization tools such as Qlik Sense, Tableau, or D3Experience with cloud-based analytics platforms, including DatabricksStrong written and verbal communication skills, including presenting insights to senior stakeholdersPreferred qualifications, capabilities, and skills Deep understanding of large language model techniques, including agents, planning, and reasoningExperience building and deploying machine learning models on AWS using tools such as SageMaker and Amazon Elastic Kubernetes Service (EKS)Advanced knowledge of reinforcement learning or meta learning